PL1

The extreme precipitation events had received priority attention due to its environmental, social and economic implications. Over the last decades, atmospheric modeling has been an essential tool to minimize their impact, with mesoscale numerical models development. However, model validation has large challenges in the case of the precipitation field. The reasons are well known, namely, precipitation measurement uncertainties, use of gridded datasets vs direct observations, statistical goodness-of-fit measures selection, etc. In this regard, accumulated precipitation throughout the event has been commonly used as an indicator of model performance. Nevertheless, because of their potentially dramatic consequences, intense sub-daily precipitation is of great importance for risk assessment. Thus, intense precipitation over a very short period often result flash floods in the Mediterranean area, for which a sub-event precipitation assessment is required. In this work hourly precipitation outputs of the WRF model has been analyzed within extreme precipitation events in Iberian Peninsula. The WRF testing was carried out considering three microphysics and two planetary boundary layer parameterizations. The results shown poor results for WRF hourly precipitation vs. observation from point to point. However, the parametrizations were relevant, with the Goddard and Thompson microphysics and MYNN PBL performing better.

How to cite: Sanchez, J. L., Merino, A., García-Ortega, E., Navarro, A., Tapiador, F. J., and Marcos, J. L.: Some tools to forecast the extreme precipitation events in the Mediterranean areas, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 18–21 Oct 2022, Plinius17-10, https://doi.org/10.5194/egusphere-plinius17-10, 2022.

Heavy precipitation events on the southern side of the Alps are typically associated with a favourable large-scale environment, characterized by an upper-level trough or cut-off cyclone over the western Mediterranean. This configuration induces, at the meso -scale, a meridional transport of large amount of moisture towards the orography, often organized in the form of a pre-frontal low-level jet. The thermodynamic characteristics of the impinging moist flow and its interaction with the orography determine the distribution and the intensity of the rainfall.

The present study shows that, besides the local contribution from the Mediterranean Sea, a relevant amount of moisture may move from the tropics towards the Mediterranean within long and narrow filament-shaped structures, known as atmospheric rivers (AR). To this aim, a detection algorithm, designed for the open oceans, has been adapted to the peculiar morphology of the Mediterranean and applied to identify ARs during some of the most severe weather events affecting the Alpine region in the last decades. Moreover, some diagnostic tools, such as an algorithm for the calculation of the atmospheric water budget, have been employed to compare and investigate such AR events.

The presence of ARs across the Mediterranean has been recently associated with heavy precipitation over southern Europe and Italy in particular. However, their role has not been fully assessed yet, in terms of contribution to the rainfall amount and of interaction with the cyclones driving their evolution. Therefore, high resolution numerical simulations are exploited to investigate how the transport of water vapour associated with the AR may have impacted on the severity and dynamics of a recent heavy precipitation event affecting the western Alps, and to disentangle how much rainfall can be attributed directly to the presence of the AR.

How to cite: Davolio, S., Miglietta, M. M., Vercellino, M., Drago Pitura, L., Giovannini, L., Sioni, F., Grazzini, F., Laviola, S., and Levizzani, V.: The role of Atmospheric Rivers in the Mediterranean in heavy precipitation events over the Alps, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 18–21 Oct 2022, Plinius17-31, https://doi.org/10.5194/egusphere-plinius17-31, 2022.

Elongated and quasi-stationary convective rainbands triggered by small-scale orography and capable of producing heavy precipitation are often observed over the Italian Alps. Such features occurred in the final and most intense phase of the Vaia storm over the eastern Italian Alps, on the evening of 29 October 2018. South-east/north-west oriented bands, driven by the strong Sirocco wind, caused floods and landslides in several locations. In the present work, the thermodynamic conditions favorable for their formation and the triggering by small-scale topographic features are investigated through semi-idealized numerical simulations with the Weather Research and Forecasting (WRF) model.

Simulations are initialized using radio-sounding data measured at Udine-Rivolto, upstream of the eastern Italian Alps, at 18:00 UTC, 29 October. The small-scale energy needed to develop convection is provided by prescribing background thermal fluctuations embedded in the low-level flow or applying random perturbations to the topographic field.

The first tests using a simplified smooth ridge highlight that rainbands develop even without the triggering effect of small-scale topographic features. The simulated convection tends to organize in non-stationary bands which result from flow-parallel roll-type circulations with tilted updrafts reaching 6-7 km altitude. A sensitivity analysis with simulations at 1, 0.5 and 0.2 km grid spacing highlights that results are independent of the model resolution.

The influence of stability, wind intensity and wind shear on the development of rainbands is also investigated, using different idealized sounding profiles in the absence of small-scale topographic triggers. Similar to previous studies, results highlight that band-shaped convection is favored in vertically sheared intense flows without rotation of wind direction with altitude and weakly unstable cap clouds. The presence of convective inhibition in the boundary layer is fundamental for constraining the release of convection over the idealized ridge. On the other hand, intense instability or saturated layers within the mid-upper part of the statically unstable cap cloud disrupt the convective organization.

The presence of small-scale topographic perturbations, capable of releasing energy in the upstream edge of the unstable cap cloud in the form of lee waves, causes stationary rainbands which enhance the spatial variability in cumulative precipitation. The intensity of convection is efficiently amplified by individual obstacles when the induced wave pattern is in phase with the forced ascent generated by the main ridge. Moreover, the coupling between induced gravity waves and low-level convergence zones due to flow channeling and deflection has been revealed effective for rainband formation.

Finally, simulations with the real eastern Alpine orography demonstrate that, under Sirocco conditions, highly stationary bands are triggered by the topographic perturbations of the south-eastern Alpine foothills, individuating the favorable location of orographic rainbands for future similar convective events.

How to cite: Degiacomi, T., Zonato, A., Davolio, S., Miglietta, M. M., and Giovannini, L.: Numerical simulations of banded orographic convection over the eastern Italian Alps: influence of atmospheric conditions and local topography, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 18–21 Oct 2022, Plinius17-29, https://doi.org/10.5194/egusphere-plinius17-29, 2022.

Liguria region in the last years has been affected by devasting floods as result of extreme precipitation events. During these events, many records in terms of precipitations amount/rates over the Italian peninsula were overtaken, such as181mm/h during the 4 November 2011 Genoa flood, and 741 mm/12h and 884 mm/24h during the 21 October 2021 Rossiglione flood.

From a synoptic point of view, similar configurations characterize the extreme events that affected Liguria region, i.e., the presence of a deep pressure minimum west of the region and a strong high pressure over eastern Europe. Such conditions are favorable to the triggering of a quasi-stationary mesoscale convective systems over the Ligurian Sea.

Furthermore, this kind of configuration is favorable to the formation and transport of wide plumes of aerosol, mainly mineral dust from the Sahara Desert and sea salt aerosols generated under high

wind condition in the Mediterranean basin.

The present study aims to evaluate the impact that these aerosol plumes can have on the triggering and evolution of the deep convective systems responsible for Liguria flooding events. This study is carried out through numerical simulations performed with the WRF (Weather Research and Forecasting)-Chem model, version 4.0.  WRF-Chem is the WRF model coupled with the Chemistry: the model simulates the emission, transport, mixing, and chemical transformation of trace gases and aerosols as well as the meteorology.

In particular, the object of the presented research is to investigate the influence that cloud-aerosol-radiation interactions may have on the physics and dynamics of the rainfall events, primarily by means of the so-called direct (aerosol-cloud) and indirect (aerosol-radiation) interactions.

For this purpose, 3 different sets of simulations were performed: a control run, in which the chemical part of WRF-Chem model has not been activated, i.e., the production and transport of aerosol and its direct and indirect effects on atmosphere are not taken into account; a run in which the dust transport is considered and only aerosol direct effect are accounted for; a final run in which both direct and indirect effects are taken into account.

How to cite: Ferrari, F., Cassola, F., Mazzino, A., Miglietta, M. M., Morichetti, M., and Rizza, U.: Evaluation of aerosol direct and indirect effects on extreme precipitation events over Liguria Region, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 18–21 Oct 2022, Plinius17-33, https://doi.org/10.5194/egusphere-plinius17-33, 2022.

While observations of Mediterranean SST (Sea Surface Temperature) are showing an increasing trend during the last decades, future CMIP6 (Coupled Model Intercomparison Project Phase 6) projections highlight a further increase of approximately 3 °C, according to the SSP3-7.0 (Shared Socioeconomic Pathway) scenario. Among the coastal areas of the Mediterranean Basin, the Calabrian peninsula (southern Italy) is particularly prone to severe hydrometeorological events due to the intense atmosphere-sea interactions, further enhanced by local complex orography.

This study evaluates how the observed and projected Mediterranean SST increase affects the precipitation patterns in Calabria. We performed four months of simulations in a particularly rainy period from September to December 2019 using WRF (Weather Research and Forecasting) model by varying the SST lower boundary conditions. First, we considered actual conditions provided by ERA5 reanalysis. Then, we hypothesised past (a homogeneous decrease of −1 °C, referring approximately to 1980) and future (a homogeneous increase of +3 °C, referring to the end of this century) SST scenarios. Other boundary conditions, also given by ERA5, were not modified.

We focused on 20 rainfall events that actually occurred during the analysed period, whose intensities and spatial patterns were affected by different SST values. Most of the more dangerous events, coming south-eastwards from the Ionian Sea, increased their intensity with higher SST, fueling the atmosphere with water vapour more efficiently. Still, due to the enhanced atmospheric instability, such events were often solved in off-shore storms before reaching the coastline. Therefore, the analysis suggests that if only the SST changes are considered, the frequency of severe inland events will increase due to the enhanced air-sea flux exchange, but the intensity will not.

Further studies will be based on improved, fully-coupled atmospheric, oceanic and hydrological modelling systems and extend the analysis to different Mediterranean regions.

How to cite: Furnari, L., Castagna, J., Mendicino, G., and Senatore, A.: Assessment of projected Mediterranean SST influence on severe precipitation events, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 18–21 Oct 2022, Plinius17-79, https://doi.org/10.5194/egusphere-plinius17-79, 2022.

Fast hydro-geomorphic hazards such as flash floods and debris flows cause numerous fatalities and large damage, and are triggered by sub-daily extreme precipitation. Projecting future changes in these extremes is thus of great importance for risk management and adaptation strategies. High-resolution climate models, called convection-permitting models (CPMs), represent land-surface characteristics and small-scale processes in the atmosphere, such as convection, more realistically than coarser resolution models. Subdaily extremes could be better represented, and thus CPMs provide higher confidence in the estimate of future changes in extreme precipitation. However, the existing CPM runs are available for relatively short time periods (10–20 years at most) that are too short for deriving precipitation frequency analyses with conventional extreme value methods.

Here, we evaluate the potential of a novel statistical approach based on many “ordinary” events rather than just yearly maxima or a few values over a high threshold. This method has the potential to provide reliably estimate of rare return levels from short data record, thus offering the chance to be effectively applied to the analysis of CPM data for reliable frequency analysis on future precipitation. We focus on an Eastern Alpine transect, characterized by a complex orography, where significant changes in sub-daily annual maxima have been already observed. We estimate future changes under the RCP8.5 scenario using COSMO-crCLIM model simulations at 2.2 km resolution. We focus on three 10-year time slices (historical 1996-2005, near-future 2041-2050, and far future 2090-2099). A bias assessment is also performed by comparing the estimated extremes from the historical time-slice to the ones from long records of observed precipitation. We estimate extreme precipitation for duration ranging from 1 h to 24 h and assess the changes between the time periods. Specifically, we analyze: annual maxima, return levels, and parameters of the statistical model.

Although the storms' frequency will generally decrease in the region, the mean annual maxima exhibit a general increase in the near and far future, especially at shorter durations. The change in the extreme return levels shows a similar trend, with larger increase in the far future at the shorter duration. Interestingly, the changes show a spatial organization that can be associated to the orographic features of the area: the stronger increasing changes are located in the high elevation zone, while in the lowlands weak decrease and weak increase emerge in the near and far future, respectively.

This analysis demonstrates the possibility to have reliable estimates of future extreme precipitation from short CPM runs by using a novel method based on ordinary-events. The relevant findings from this analysis are useful for improving our knowledge about the projected future changes in extreme precipitation and thus for improving the strategies for risk management and adaptation.

How to cite: Dallan, E., Roghani, B., Fosser, G., Schaer, C., Marani, M., Borga, M., and Marra, F.: Future changes in sub-daily precipitation return levels over an alpine transect from a convection-permitting model, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 18–21 Oct 2022, Plinius17-67, https://doi.org/10.5194/egusphere-plinius17-67, 2022.

The recent decade has witnessed an overwhelming increase in convective storms such as heavy rains, hailstorms, tornadoes, strong winds, and lightning leading to extreme weather events around the globe. Principally, the thunderstorm producing cloud is the main environment in which these convective storms related to extreme weather events develop. Convective storms characterize the deadliest extreme weather events that pose wider socio-economic risks and impacts resulting in disruptions of social functions and services, damage to properties and infrastructures, injuries, and loss of life to people. However, the predictability of such extreme weather events still presents the most challenging task in operational weather forecasting. Thus, accurate and reliable forecasts of such weather phenomena are of critical importance to mitigate the adverse impacts and risks associated with extreme weather events. 

The current work is intended to simulate the convective weather storms pertaining to hailstorms, lightning, tornadoes, and strong winds that hit the Northwest part of Italy during the most recent decade. The emphasis will be placed on the Ligurian region, which is among the regions forming the North-west part of Italy with complex weather systems.  The high-resolution Numerical Weather Prediction (NWP) model, namely the Advanced Research of the Weather and Research Forecasting (ARW) modeling system will be used to simulate such weather events. The study will amount to two tasks. The very earliest task will investigate the implications of three resolutions (10 km, 3.3 km, and 1.1 km) of the ARW modeling system in simulating such weather phenomena. The latter task will use the obtained resolution to further investigate the implications of different parameterization schemes of the microphysics category in the ARW model. Observed data and/or reports from reliable sources will be used to verify the simulations from the ARW model using various approaches. Different results from diverse approaches will be presented and discussion will be performed based on the results obtained. Finally, the conclusion will be drawn based on the results and discussions.

How to cite: Tuju, P. E., Ferrari, F., and Mazzino, A.: Predictions of Extreme Weather Events in a Climate Change Environment in the Northwest Italy, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 18–21 Oct 2022, Plinius17-50, https://doi.org/10.5194/egusphere-plinius17-50, 2022.

The METEO unit of the National Observatory of Athens has developed a methodology for ranking rain storms in Greece, following a similar procedure in the USA, where ranking of snow storms is routinely performed. The rain storm ranking in Greece is performed through the calculation of the Regional Precipitation Index (RPI) which takes into account:

a)         The daily accumulated precipitation and its exceedance of specific percentile thresholds.

b)         The total area where these exceedances occur.

c)         The population of the area that these exceedances occur.

First, RPI calculations were applied in ERA5-Land rainfall re-analysis, available at 0.1 deg resolution, for a 30-year period spanning from 1991 to 2020 and all major storms that occurred within this period were ranked and correlated to the reported societal impacts. The ranking of the storms is performed based on the percentiles of all non-zero RPI in the examined period. As major storms we define the top 2% of RPI. Then, a proposed methodology for the application of the methodology on daily forecast fields provided by high-resolution numerical weather prediction models is tested and discussed. This work, was funded by the European Climate Foundation.

How to cite: Lagouvardos, K., Papavasileiou, G., Kotroni, V., Papagiannaki, K., Dafis, S., and Galanaki, E.: Regional Precipitation Index: ranking storms in Greece, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 18–21 Oct 2022, Plinius17-32, https://doi.org/10.5194/egusphere-plinius17-32, 2022.

The classification of Mediterranean cyclones has always been a challenging task, especially when grouping warm-core and small-scale cyclones such as the Mediterranean tropical-like cyclones (Medicanes). The sudden intensity changes of Medicanes, the evolution of deep convection and the large spread of forecast tracks in numerical weather forecast models highlight the challenges in understanding the dynamics of these weather systems. In this study, numerical diagnostics are used to explain the evolution and contribution of diabatic processes in case studies of Medicanes. High-resolution simulations with WRF model are utilized and are evaluated against observations, before implementing the Pressure Tendency Equation (PTE). The decomposition of PTE shows interesting results about the contribution of diabatic processes and large-scale forcing during each Medicane. Moreover, an online Potential Vorticity (PV) tracer module is implemented in the WRF model, that provides another metric for the role of latent heating during the same Medicanes. Both approaches help to identify important differences among the case studies and shed a new light on a new pathway of Medicane development.

How to cite: Dafis, S., Flaounas, E., Claud, C., Kotroni, V., and Lagouvardos, K.: Quantifying the contribution of diabatic processes in the intensification of Mediterranean tropical-like cyclones (Medicanes), 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 18–21 Oct 2022, Plinius17-69, https://doi.org/10.5194/egusphere-plinius17-69, 2022.

Over the Mediterranean basin we can occasionally observe intense cyclones showing tropical characteristics and known as Mediterranean Tropical-Like Cyclones (TLC). Previous studies focusing on past TLCs events have found that SST anomalies play a fundamental role in modulating the intense air-sea exchange of latent and sensible heat fluxes, hence controlling both development and evolution of TLCs. However, given the connection between ocean mixed layer, ocean heat content and temperature, it is important to explore also the role of the mixed layer depth (MLD). In this study we investigated the role of both SST, SST anomaly and MLD profile on genesis and evolution of a recent record-breaking TLC. Specifically, we focus on TCL “IANOS”, a cyclone that originated over the southern Ionian Sea around 14 Sept 2020, moved over the Central Ionian Sea from south-west to North-East, and made landfall around 19 Sept 2020 over Greece mainland coast. It developed over a basin where a positive SST anomaly up to 4 °C was detected, which coincided with the sea area where it reached the maximum intensity. We conducted a series of experiments using an atmospheric model (WRF - Weather Research and Forecasting system) driven by underlying SST (standalone configuration) with daily update or coupled to a simple mixed-layer ocean model (SLAB ocean), with SST calculated at every time step using the SLAB ocean for a given value of the MLD. WRF was implemented with 3 km grid spacing, forced with ECMWF-IFS analysis (9 km resolution), while SST or MLD initialization, for standalone or coupled runs, respectively, are provided by the MFS-CMEMs Copernicus dataset at 4 km of horizontal resolution. For the studied TLC, the mean MLD is modified by increasing or decreasing its depth by 10 m, 30 m, 50 m, 75 m, 100 m, change the lapse rate ot MDL and studi the impacto of SST and anomaly present and estimated by climatological projections; the preliminary results show that the MLD influences not only the intensity of the cyclone but also the structure of the precipitation field both in terms of magnitude and location. At first  the MLD thickness was characterized  for the days in which the cyclone developed using ocean modeling data. Then we identified possible past and future climatological scenarios of MLD thickness. Starting from these data, we simulated the impact of the MLD, and consequently of the Ocean Heat Content, on the TLC. The preliminary results show that the MLD influences not only the intensity of the cyclone but also the structure of the precipitation field both in terms of magnitude and location. The results deserve further investigation in particular in the context of climate change scenarios.

How to cite: Ricchi, A., Liguori, G., Cavicchia, L., Miglietta, M. M., Bonaldo, D., Carniel, S., and Ferretti, R.: On the influence of Ocean Mixed Layer depth and Sea Surface Temperature Anomaly in the genesis and evolution of the Mediterranean Tropical-Like cyclones “IANOS”, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 18–21 Oct 2022, Plinius17-18, https://doi.org/10.5194/egusphere-plinius17-18, 2022.

Subtropical cyclones (STCs) are low-pressure atmospheric systems characterized by having a hybrid structure that shares tropical and extratropical features. Due to their rapid intensification and harmful impacts, sometimes similar to those generated by tropical storms or even hurricanes, the implementation of accurate simulations becomes key for improving their forecast. In this study, a particular STC developed in October 2014 near the Canary Islands is analyzed using the high-resolution HARMONIE-AROME model. This model is developed and operated at 2.5 km resolution through the collaboration of the 10 European National Meteorological Services (NMS) that are part of the international research program HIRLAM together with the 16 countries that comprise the ALADIN consortium. The HARMONIE-AROME model has a convection-permitting configuration and uses a non-hydrostatic spectral dynamical core with a semi-Lagrangian and semi-implicit discretization of the equations, which implies a lower computational cost. In order to evaluate the environment in which the cyclone was formed, several convective tools are used. In addition, the cyclone phase space diagrams (CPS) are used to thermodynamically categorize the STC as a hybrid system. Furthermore, considering the difficulty of obtaining observational data in the vicinity of this type of system, most of the time located in the middle of the ocean, the use of satellite data becomes key for the validation of the model’s simulations. Consequently, in this study, the simulated cloud top height is assessed for the October 2014 STC.

How to cite: Quitián Hernández, L., Calvo-Sancho, C., Díaz Fernández, J., Bolgiani, P., Santos-Muñoz, D., Gonzalez-Alemán, J. J., Sastre, M., Valero, F., Farrán, J. I., and Martín Pérez, M. L.: Analysis of a subtropical cyclone in the North Atlantic Ocean by means of the HARMONIE-AROME model: evaluation against satellite data, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 18–21 Oct 2022, Plinius17-41, https://doi.org/10.5194/egusphere-plinius17-41, 2022.

On the evening of November 12, 2019, an exceptional high tide hit the city of Venice and the central-southern area of its lagoon, damaging a large part of its historical center. The main cause of the event was a small warm-core mesoscale cyclone, which formed in the central Adriatic Sea and intensified during its northwestward movement. 

Simulations with different initialization times were carried out with the Weather Research and Forecasting (WRF) model, showing a strong sensitivity to the initial conditions, since the track (and strength) of the cyclone was determined by the exact position of an upper-level potential vorticity (PV) streamer. The factors responsible for the cyclone development are also investigated. The pre-existence of positive low-level cyclonic vorticity, associated with the convergence of the Sirocco and Bora winds in the Adriatic, made the environment favorable for cyclone development. Also, the interaction between the upper-level PV anomaly and the low-level baroclinicity, created by the advection of warm, humid air associated with the Sirocco, was responsible for the cyclone’s intensification, in a manner similar to a transitory (stable) baroclinic interaction at small horizontal scales.

Conversely, convection and sea surface fluxes did not play a significant role, thus the warm-core feature appears mainly as a characteristic of the environment in which the cyclone developed rather than a consequence of diabatic processes. The cyclone does not fall into any of the existing categories for Adriatic cyclones.

How to cite: Miglietta, M. M., Buscemi, F., Dafis, S., Papa, A., Tiesi, A., Conte, D., Davolio, S., Flaounas, E., Levizzani, V., and Rotunno, R.: A high-impact meso-beta vortex in the Adriatic Sea, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 18–21 Oct 2022, Plinius17-3, https://doi.org/10.5194/egusphere-plinius17-3, 2022.

The Mediterranean Sea is a mid-latitude fairly temperate marine basin, strongly influenced by the North-Atlantic atmospheric circulations. In this semi-enclosed basin, a wide variety of cyclogenesis mechanisms are known to develop, including baroclinic waves coming from the Atlantic, Mediterranean cyclogenesis originating from the cut-off of baroclinic waves, Tropical-Like Cyclones (TLC), Rapid-Cyclogenesis (RC) and Intense Mediterranean Cyclones (IMC). Depending on the cyclone type, the characteristic frequency of appearance can vary, ranging from tens per month to 1.5 per year, as in the TLC case. RCs are among the rarest and probably most intense and destructive cyclogenesis events that can develop within the Mediterranean basin; they usually originate at high latitudes, during wintertime, and mainly over the sea, preferring areas with high Sea Surface Temperature (SST) gradients. It is generally accepted that these events are determined by 12 different parameters, among which the most relevant one is the quick drop of pressure, close to 1hPa/hr for 24 hours, within the eye of the cyclone. RCs formation is an extremely complicated process, and in the Mediterranean basin it is mostly driven by air intrusions from the stratosphere and by the presence of Atmospheric Rivers. Using ERA5 dataset, we firstly conducted a physical and dynamical analysis of the most intense cyclogenesis events occurred in the Mediterranean basin in the period 1979-2020, identifying factors which triggered, generated cyclones and contributed to the intensification of such events. According also to Sanders’ and Gyakum’s definition of Bergeron, a parameter which describes RCs’ deepening rate and varies from 28mb (24h)^-1 at the pole to 12 mb (24h)^-1 at latitude 25°N, we were able to classify them in the three aforementioned categories. Further analysis has been undertaken to determine the cyclones’ phase and their main morphological characteristics, as well as their statistical distribution, seasonality and correlation with relevant indexes such as NAO, EA and SCAND, as well as  SST anomalies exhibited by the Central Mediterranean Basin.

How to cite: Carniel, C. E., Ferretti, R., Ricchi, A., Curci, G., Serafini, P., Wellmeyer, E. D., and Zardi, D.: Analysis and classification of severe cyclogenesis events over the western Mediterranean Sea in the last 40 years, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 18–21 Oct 2022, Plinius17-20, https://doi.org/10.5194/egusphere-plinius17-20, 2022.

In the last decades, the intensity and frequency of extreme weather events have increased in Europe. The climate change, through its impact on the atmospheric processes, is expected to lead to further increase of such severe phenomena which also affect the air traffic activities. Therefore, a continuous monitoring and understanding of convective and pre- convective environment is highly demanded and indeed several studies have been made towards this direction. However, there are still gaps and uncertainties, especially regarding extreme weather events that are locally developing in a short time range. The nowcasting of extreme weather is a difficult task due to the complex structures and non-linear relation between its features. The existing weather numerical models are computationally expensive and limited by the difficulty to transform the acquired knowledge into accurate mathematical equations. For these reasons, this topic has gradually gained attention in the artificial intelligence community which aims at establishing more accurate models than the existing well-known techniques.

Within the H2020 SESAR multi-hAzard monitoring and earLy wARning system (ALARM) project, we focus on nowcasting the rain and wind speed using different algorithm input configurations that account for convective and pre-convective environments using data from weather stations, lightning detectors, radar and GNSS receivers with 10-minute sampling rate. The selected areas are Milano Malpensa and Brussels Zaventem airports, where extreme weather events are highly active. With the good quality datasets available for 10 years, we built an end-to-end spatio-temporal nowcasting model that ensembles independent Long Short Term Memory based encoder decoder sub-models to predict rain and wind speed absolute values up to 1 hour ahead given 2 hours of past observations.

Following the regression analysis of the predicted features, we classify rain and wind speed extremes events and we present the assessment of the nowcasting model in terms of the probability of detection, false alarm ratio and the critical success index. For specific case studies we also showcase the potentials of the model as a useful tool for aviation management. The results show excellent wind speed nowcasting performances with probability of detection higher than 90% and false alarms ranging from 1% to 3%. The rain nowcasting model underestimates the observations but a post-processing adjustment allows to reach probability of detection higher than 80% and about 10% of false alarms.

How to cite: Chkeir, S., Anesiadou, A., and Biondi, R.: Spatio-temporal nowcasting of local severe weather events with deep neural networks, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 18–21 Oct 2022, Plinius17-12, https://doi.org/10.5194/egusphere-plinius17-12, 2022.

Situated in the eastern Mediterranean basin, Greece is characterized by pronounced increasing trends in heat waves intensity, duration and frequency of occurrence. This evidence-based fact is associated with the human-induced climate change (CC). However, CC is not responsible for every single extreme temperature event. Attributing weather extremes to manmade climate change is necessary for putting CC effects in context. It is also of paramount importance for addressing societal needs and providing actionable knowledge to governance authorities with respect to the CC impact on humanity. The traditional attribution processes that are based on climate modeling are computationally demanding and very challenging in terms of uncertainty quantification. For this, in the current work, we present a forecast-based storyline methodology and demonstrate its application for the extreme nine-day (July 25-August 08) heat wave that affected Greece in summer 2021. The method is based on the Weather Research and Forecasting (WRF) model, which is operationally applied over Greece and neighboring countries at high spatial resolution (2 km) for supporting the NOA (National Observatory of Athens) weather forecasting activities. WRF has successfully predicted the event of interest, providing robustness in the attribution analysis. We first define and simulate analogues of the examined episode under hypothetical climate settings. For the past experiment, this corresponds to the simulation of the heat wave under pre-industrial global CO­_2­ concentrations and historical simulated Sea Surface Temperature (SST). For the future experiment, the CO­_2­ concentrations during the forecast simulations were set equal to those anticipated on 2050 based on the shared socioeconomic pathway 2 - 4.5 (SSP2-4.5), while SST was set based on future simulations. Then, we compare the 2021 extreme heat wave to the past and future scenarios, and investigate differences in the heat wave amplitude, attributed to the anthropogenic forcing.

How to cite: Giannaros, C., Dafis, S., Galanaki, E., Kotroni, V., Lagouvardos, K., and Giannaros, T. M.: Attribution of the extreme heat wave of July-August, 2021, in Greece to human-induced climate change, employing a forecast-based storyline approach, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 18–21 Oct 2022, Plinius17-55, https://doi.org/10.5194/egusphere-plinius17-55, 2022.

Drought is a complex and multifaceted natural phenomenon whose effects may have serious environmental and socio-economic impacts on communities. Drought is a multi-year phenomenon and thus its probabilistic characterization needs long instrumental records. As a possible way to overcome the limitation posed by the paucity of long-term historical records of hydro-meteorological variables, in this work we aim at using paleo-climate reconstructions from tree-ring records, which are becoming increasingly available (International Tree-Ring Data Bank, ITRDB, accessible from the repositories of the NOAA's National Centers for Environmental Information). On the other side, we attempt to find the statistical link of paleo-climate data with drought characteristics identified on indices largely used in the literature, such as the self-calibrating Palmer Drought Severity Index (scPDSI). In particular, we determine drought events and their properties (severity, duration, and intensity) using threshold methods based on the statistical “theory of runs”. We then explore the potentialities of using the recently-proposed Metastatistical Extreme Value Distribution (MEVD) to estimate the probability of occurrence of extreme drought events of different severity, duration, or intensity at several European sites. Unlike the statistical approaches based on the traditional Extreme Value Theory, the MEVD framework minimizes estimation uncertainty by leveraging the information content of all the ordinary values (i.e., those in the main body of the probability distribution).

More in detail, in this work we focus on: (1) tests of the reliability of these paleo-climatic reconstructions in reproducing meteorological droughts in long observational records, (2) the statistical analysis approach affording minimal uncertainty in the estimation of extreme drought events with an assigned probability of exceedance, and (3) how the severity and timing of impacts vary across and within drought-affected areas.

How to cite: Caruso, M. F., Peres, D. J., Cancelliere, A., and Marani, M.: Extreme meteorological droughts from paleo-climatic reconstructions analyzed through non-asymptotic extreme-value distributions, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 18–21 Oct 2022, Plinius17-86, https://doi.org/10.5194/egusphere-plinius17-86, 2022.

The distribution of cloud-to-ground lightning energies is well established, and its most extreme values appear only in extremely rare flashes (< 0.0001%), defined as lightning "super-bolts". There are varying definitions of the specific energy values of super-bolts, depending on the detector or mode of observation. When using optical energy as viewed from a satellite, one usually refers to the brightest flashes (10³ times brighter than average), while when relating to the electromagnetic radiation received by lightning detection networks, the definition revolves around the strongest signals in the VLF or ELF range, or the largest peak-current or charge-moment-change (CMC) inferred from the signal. These are all different metrics for evaluating the lightning's intensity, and they are inter-related and exhibit mutual dependence (e.g. extreme values of peak current positively correlate with extreme VLF amplitudes).

The global distribution of these extremely powerful lightning is remarkably different from that of normal lightning, which are concentrated in the 3 convective "chimneys" of tropical Africa, South America and the maritime continent in South-east Asia. Superbolts are found mostly over the oceans and near coastlines, such as Sea of Japan, the North Sea and in the Andes mountains (Holzworth et al., 2019). They are also discovered in maritime winter storms over the Mediterranean Sea, which is one of the most prolific regions, especially in the months November-January.

We present the climatology of east-Mediterranean super-bolts (peak current > 200 kA), and compare data obtained by various lightning detection networks (ENTLN, WWLLN and ILDN). Some storms exhibit a larger percentage of superbolts compared with the global average, up to 0.65% of total flashes. While the physical mechanisms producing these powerful flashes remains unknown, we suggest that such flashes are more common when large amounts of desert dust aerosols, coming from the Sahara Desert, are ingested into maritime winter cyclones and contribute to convective invigoration, enhanced freezing and efficient charge separation. Initial modelling results will be discussed.

How to cite: Yair, Y., Price, C., Lynn, B., Kurzets, M., and Namia-Cohen, Y.: The frequency of lightning super-bolts in winter thunderstorms associated with Mediterranean cyclones, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 18–21 Oct 2022, Plinius17-14, https://doi.org/10.5194/egusphere-plinius17-14, 2022.

A new lightning-flash and convective initiation climatology is developed over the Alpine area, one of the hotspots for lightning activity in Europe. The climatology uses cloud-to-ground (CG) data from the European Cooperation for LIghtning Detection (EUCLID) network, occurring from 2005 to 2019.  The CG lightning data are gridded at a resolution of approximately 2km and 10min. A new and simple method of identifying convective initiation (CI) events applies a spatiotemporal mask to the CG data to determine CI timing and location.
Although the method depends on a few empirical thresholds, sensitivity  tests show the results to be robust. The maximum activity for both CG flashes and CI events is observed from mid-May to mid-September, with a peak at the end of July; the peak in the diurnal cycle occurs in the afternoon. CI is mainly concentrated over and around the Alps, particularly in northern and northeastern Italy. Since many thunderstorms follow the prevailing mid-latitude westerly flow, a peak of CG flashes extends from the mountains into the plains and coastal areas of northeastern Italy and Slovenia. CG flashes and CI events over the sea/coast occur less frequently than in plains and mountains, have a weaker diurnal cycle, and have a seasonal maximum in autumn instead of summer.

How to cite: Manzato, A., Serafin, S., Miglietta, M. M., Kirshbaum, D., Schulz, W., and Fasano, G.: A pan-Alpine climatology of lightning and convective initiation, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 18–21 Oct 2022, Plinius17-37, https://doi.org/10.5194/egusphere-plinius17-37, 2022.

Hailpads networks allow knowing the characteristics of the stones precipitated by hail storms. The province of Lleida (Spain) has an excellent network of hailpads (managed by the ADV Terres de Ponent and the Servei Meteorologic de Catalunya) which is located south of the Pyrenees. To the north of it and in French territory, there is another similar one (placed in Hautes Pyrénées and Midi Pyrénées), managed by ANELFA. A large part of the hail storms that affect this French area are formed in Spanish territory, crossing the mountainous barrier of the Pyrenees, so it is interesting to know their characteristics from one side to the other. In both cases, historical series of more than 20 years are available.

We have taken the database of all the days in which hail falls have been detected in one or another hailpads network and we have calculated the diameter and maximum energy of the precipitated stones. With the data obtained, we have found the corresponding statistical distributions.

Once we have obtained these four databases (ie two for each of the networks) we have analyzed the statistical parameters that characterize them. We have also studied the temporal trend of hail precipitation on both sides of the Pyrenees

Finally, we have studied the meteorological factors that intervene in the formation of hail and the dependence they have on the maximum diameter and the maximum expected energy.

The results show a greater severity in the stones precipitated on the South side of the Pyrenees and the meteorological factors involved in the formation of hailstorms.

How to cite: Marcos-Menéndez, J. L., Sánchez, J. L., Merino, A., García-Ortega, E., Navarro, A., Berthet, C., and Dessens, J.: Comparison of the characteristics of hailstones precipitated on one side and the other of the Pyrenees., 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 18–21 Oct 2022, Plinius17-40, https://doi.org/10.5194/egusphere-plinius17-40, 2022.

Lightning is an important threat to life and properties and its forecast is important for practical applications. We show the performance of a dynamic lightning scheme for the next-day strokes forecast. The prediction is compared against the LINET network, and the forecast period spans one year. Specifically, a total of 162 case studies were selected between 1 March 2020 and 28 February 2021. The events span a wide range of lightning intensity; 69 cases occurred in summer, 46 in fall, 18 in winter, 29 in spring.

Three different settings of the lightning scheme are considered to test the sensitivity of the method to the key parameter of charge transferred in 1 second: 0.5*10^-4 C (L50), 0.75*10^-4 C (L75),  and 1.0*10^-4 C(L100).

The meteorological driver is WRF. Each simulation lasts 36h and the first twelve hours are the spin-up time and are discarded from the analysis. The focus is on the next-day forecast (12-36 h). The horizontal resolution of the simulations is 3 km and 50 unevenly spaced vertical levels extend from the surface to 50 hPa.

Lightning is closely related to convection in the atmosphere and model errors in the lightning forecast have two main sources: errors in forecasting the convection and errors in the representation of the electric processes inside the clouds. This makes the lightning forecast a difficult task.

Results are discussed for the whole year and for different seasons. Moreover, statistics are presented for the land and sea. LINET strokes are remapped into the WRF 3km grid and then further elaborated for comparison with the strokes forecast.

Among the three configurations of the lightning scheme, L75 forecasts accurately the total number of strokes recorded for all the cases, L50 underestimates the strokes and L100 overestimates the strokes. The time-series correlation of daily observed and forecasted strokes is around 0.75 and depends on the season.

Qualitative scores (FBIAS, ETS, POD, FAR) computed for the 3km grid and different strokes thresholds have low values and upscaling the model output, by summing the forecast and observed strokes over grids with larger grid spaces (from 6 to 48 km), improves the results. Among the different configurations of the dynamic lightning scheme, L75 performs slightly better. However, L50, L75, and L100 show very similar spatial patterns of predicted strokes.

The analysis of the fraction skill score shows that the best lightning forecast is for summer, followed by fall, winter, and spring. This happens for all configurations L50, L75, L100.

The lightning forecast performance varies between sea and land; the analysis of the Taylor diagram shows better performance over the land than over the sea. This result shows that the convection is better simulated over the land than over the sea, where the effect of topography, partially represented by the model, may focus the convection on specific areas.

The result of this study shows that lightning forecast with the dynamic lightning scheme can be performed with success in Italy; nevertheless, a careful inspection of the forecast performance is necessary for tuning the scheme to the specific purpose.

How to cite: Federico, S., Torcasio, R. C., Lagasio, M., Lynn, B. H., Transerici, C., Puca, S., and Dietrich, S.: A year-long total lightning forecast over Italy made with a dynamic lightning scheme using the WRF model, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 18–21 Oct 2022, Plinius17-2, https://doi.org/10.5194/egusphere-plinius17-2, 2022.

Extratropical cyclones are the main drivers of mid-latitude weather and they are the key synoptic phenomena that give rise to the areas of strong instability by the passage of their associated fronts. The importance of studying their characteristics in terms of development, trajectories and spatio-temporal distributions, has long been recognized over the last decades. Similarly, research of extreme events associated with extratropical cyclones has gained even more importance in the last years because of the increasing confidence that these weather systems are being affected by climate change. This relationship between extratropical cyclones and ongoing climate change might amplify their negative impacts on the largely populated midlatitude areas in the near future. To overcome time-consuming and subjective analyses of extratropical cyclones by manual analysis of synoptic maps, several numerical algorithms have been developed and used to identify and track cyclones. The procedures vary greatly with respect to computational details and the degree of sophistication involved. In many cases cyclonic cores are defined in terms of pressure minima at sea level, while in other cases they are alternatively defined in terms of maxima in low level vorticity. For this analysis, an algorithm originally developed for the identification and tracking of cyclones and pressure depressions in the Southern Hemisphere is applied to the Mediterranean region, which is considered as one of the major climatic hot spots in the world and one of the most prominent areas around the globe in terms of high-impact weather phenomena. The main goal of the current research is to derive a climatology of all cyclones and pressure depressions passing over the western Mediterranean that subsequently affect the Ligurian region and its surroundings. Several studies demonstrated that the specific geography of this area in the Mediterranean enhances the formation of intense cyclones associated with heavy rainfalls and windstorms. More precisely, the morphological characteristics of the area serve as a natural constraint to the air flows that blow from the southern quadrants and thereby creates convergence zones at low levels that affects the behaviour of meteorological structures at mesoscales. Our aim is to better understand the atmospheric conditions at larger scale that provide the necessary ingredients for the development of strong high-impact weather events. Moreover, we are interested in determining if these events have a trend in terms of their frequency and intensity, as well as a trend in the development of specific recurrent synoptic patterns that trigger mesoscale phenomena associated with high-impact weather in this area. In this sense, one of the goals of the present analysis will be to investigate the means by which the ongoing global warming causes variations of cyclonic properties and to what extent these variations affect the mesoscales associated with high-impact weather events in the region of interest.

How to cite: Hourngir, D., Burlando, M., and Romanic, D.: Climatology of high-impact weather events in the Ligurian Sea, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 18–21 Oct 2022, Plinius17-64, https://doi.org/10.5194/egusphere-plinius17-64, 2022.