17th Plinius Conference on Mediterranean Risks  

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, 12–15 Oct 2021, Plinius17-10, https://doi.org/10.5194/egusphere-plinius17-10, 2021.

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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, 12–15 Oct 2021, Plinius17-31, https://doi.org/10.5194/egusphere-plinius17-31, 2021.

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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, 12–15 Oct 2021, Plinius17-29, https://doi.org/10.5194/egusphere-plinius17-29, 2021.

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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, 12–15 Oct 2021, Plinius17-32, https://doi.org/10.5194/egusphere-plinius17-32, 2021.

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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, 12–15 Oct 2021, Plinius17-33, https://doi.org/10.5194/egusphere-plinius17-33, 2021.

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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, 12–15 Oct 2021, Plinius17-79, https://doi.org/10.5194/egusphere-plinius17-79, 2021.

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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, 12–15 Oct 2021, Plinius17-67, https://doi.org/10.5194/egusphere-plinius17-67, 2021.

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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, 12–15 Oct 2021, Plinius17-50, https://doi.org/10.5194/egusphere-plinius17-50, 2021.

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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, 12–15 Oct 2021, Plinius17-69, https://doi.org/10.5194/egusphere-plinius17-69, 2021.

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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, 12–15 Oct 2021, Plinius17-18, https://doi.org/10.5194/egusphere-plinius17-18, 2021.

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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, 12–15 Oct 2021, Plinius17-41, https://doi.org/10.5194/egusphere-plinius17-41, 2021.

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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, 12–15 Oct 2021, Plinius17-3, https://doi.org/10.5194/egusphere-plinius17-3, 2021.

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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, 12–15 Oct 2021, Plinius17-20, https://doi.org/10.5194/egusphere-plinius17-20, 2021.

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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, 12–15 Oct 2021, Plinius17-12, https://doi.org/10.5194/egusphere-plinius17-12, 2021.

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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, 12–15 Oct 2021, Plinius17-55, https://doi.org/10.5194/egusphere-plinius17-55, 2021.

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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, 12–15 Oct 2021, Plinius17-86, https://doi.org/10.5194/egusphere-plinius17-86, 2021.

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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, 12–15 Oct 2021, Plinius17-14, https://doi.org/10.5194/egusphere-plinius17-14, 2021.

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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, 12–15 Oct 2021, Plinius17-37, https://doi.org/10.5194/egusphere-plinius17-37, 2021.

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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, 12–15 Oct 2021, Plinius17-40, https://doi.org/10.5194/egusphere-plinius17-40, 2021.

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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, 12–15 Oct 2021, Plinius17-2, https://doi.org/10.5194/egusphere-plinius17-2, 2021.

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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, 12–15 Oct 2021, Plinius17-64, https://doi.org/10.5194/egusphere-plinius17-64, 2021.

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Accurate precipitation estimates are paramount for the activities related to water management and risk assessment. Satellite-based rainfall estimates are generally obtained by an inversion of the atmospheric signals reflected or radiated by atmospheric hydrometeors, i.e., a “top-down” approach. The main drawback of this retrieval technique is related to the number of satellite overpasses, that may lead to a general underestimation of rainfall.

To overcome these issues, recently, some studies have investigated the possibility to integrate the state-of-the-art rainfall products with rainfall estimates obtained by a consolidated “bottom-up” approach, SM2RAIN (Brocca et al., 2014) exploiting satellite soil moisture observations for obtaining accumulated rainfall estimates. The integration between top-down and bottom-up estimates can produce a more reliable rainfall product for hydrological applications, characterized by better estimation of rainfall amounts and timing. 

On this basis, the Satellite Application Facility on Support to Operational Hydrology and Water Management (H SAF) has started the development and the sharing of integrated datasets of top-down satellite-based precipitation and soil moisture-derived rainfall estimates.

During the Continuous Development and Operational Phase (CDOP) 3 and 4, the H SAF consortium planned to develop and provide several integrated products to the users for hydrological applications, also by taking advantages of the next EPS-SG instruments with enhanced retrieval capabilities.

In this study, the usefulness of integrated products for river discharge simulation is assessed in Italy. More in details, the integrated product between SM2RAIN-derived estimates and Passive Microwave auxiliary product H67 (H64), the gauge corrected version (H84) and the SM2RAIN-only derived product (H87), along with the parent products will be use to force a semidistributed rainfall-runoff model (MISDc) during the period 2016-2019. The obtained river discharge timeseries have been compared with observed ones in order to evaluate the skill of the investigated products showing confirming the added value of using an integrated rainfall product for hydrological applications. Moreover, the results will provide useful insight that will help in improving the integrated products.

The analysis provided good results, confirming the added value of using an integrated rainfall product for hydrological applications, allowing to overcome some of the limitations of the state-of-the-art precipitation datasets.

How to cite: Ciabatta, L., Camici, S., Filippucci, P., Massari, C., D'Adderio, L. P., Panegrossi, G., Mosaffa, H., and Brocca, L.: Satellite soil moisture-derived rainfall for flood modelling in italy, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 12–15 Oct 2021, Plinius17-56, https://doi.org/10.5194/egusphere-plinius17-56, 2021.

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Pluvial floods (PFs) caused by extreme overland flow inland account for half of all flood damage claims each year, equally with fluvial floods (FFs). However, most remote sensing-based flood detection techniques only focus on the identification of degradations and/or water pixels in the close vicinity of overflowing streams. Geomatics hydrological models have been developed to easily and widely map susceptibility towards the occurrence of intense surface runoff without physics-based modelling. However, in order to increase confidence in such methods, they need to be comprehensively evaluated using PF observations from past events. For this, a generalized remote sensing fusion method called FuSVIPR (Fusion of Sentinel-2 & Very high resolution Imagery for Pluvial flood detection in Runoff prone areas) is developed. Based on 10 m change detection (from Sentinel-2) and sub-metric optical imagery (from Pléiades satellites and airborne sensors), machine learning (ML) and deep learning (DL) techniques are used to locate PF footprints on the ground at 0.5 m spatial resolution following heavy weather events. Post processing involving land use, soil type and topography allows accounting for runoff production processes to induce PFs downstream. In this work, six watersheds in the Aude and Alpes-Maritimes departments in the South of France are investigated over more than 3000 km² of rural and periurban areas during three flash-flood events between 2018 and 2020. With a unique learning sample from the Aude flash-floods of October 2018, overall detection accuracies greater than 86% and false detection rates below 7% are reached independently on all three distinct events. These results emphasize the high generalization capability of this method to locate PFs at any time of the year and over diverse regions worldwide. The resulting damage proxy maps have high potential for helping precipitation downscaling and thorough evaluation and improvement of surface water inundation models at very high spatial resolution.

How to cite: Cerbelaud, A.: Multi-sensor optical remote sensing for generalized sub-metric detection of pluvial flood damages using U-net CNN and Random Forest., 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 12–15 Oct 2021, Plinius17-68, https://doi.org/10.5194/egusphere-plinius17-68, 2021.

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The accurate quantification of hydroclimatic risk requires detailed knowledge on the spatiotemporal characteristics of extreme rainfall. In engineering design, Intensity-Duration-Frequency (IDF) curves are fundamental tools that encompass information on rare precipitation events over a wide range of characteristic temporal scales and exceedance probability levels. Inspired by physical evidence and laws of thermodynamics, researchers widely suggest that the rapidly changing climate instigates more frequent and intense precipitation-related natural hazards. Based on the foregoing implication, current protection standards may be systematically threatened in the upcoming years. Under this non-stationary setting, several IDF estimation approaches have been proposed that allow for distribution parameter estimates to vary (in most cases linearly) with time. Yet, the introduction of additional model parameters increases the estimation uncertainty of rainfall intensity quantiles, especially for rare events. As a potential solution to limitations related to non-stationarity, Emmanouil et al. (2022) proposed an elaborate parametric approach founded on multifractal (MF) scaling arguments (see Langousis et al., 2009), which assumes that the statistical structure of rainfall at interannual scales can be approximated by sequential realizations of a stationary multifractal process with parameters that vary slowly across (not within) realizations. The suggested framework is particularly robust when describing the intensity and frequency of extreme rain rates from small precipitation samples (i.e., down to 2 years; see Emmanouil et al., 2020) and, therefore, it can be effectively applied to adequately short sequential segments of data, allowing for climatic variations to be revealed. Given the above, we attempt to expand the analysis of Emmanouil et al. (2022) toward evaluating the effects of future climate pathways on extreme rainfall, under a wide spectrum of topographical and climatological conditions. To do so, we derive IDF curves based on statistically downscaled estimates of multiple climate model outputs (e.g., Mearns et al., 2017) that cover a 120-year period (i.e., from 1979 to 2099) over the Contiguous United States (CONUS). The yielded outcomes for both historical data and climate model hindcasts exhibit that, on average, extreme rainfall displays similar trends over the study domain. However, it is shown that the dependence structure and variability of rare precipitation events vary significantly across data sources, and should be scrupulously delineated when assessing how existing risk considerations could actually be affected.

References

• Emmanouil, S., A. Langousis, E.I. Nikolopoulos, and E.N. Anagnostou (2020) Quantitative assessment of annual maxima, peaks-over-threshold (PoT) and multifractal parametric approaches in estimating intensity-duration-frequency (IDF) curves from short rainfall records, Journal of Hydrology, 589, 125151, doi: 10.1016/j.jhydrol.2020.125151.
• Emmanouil, S., A. Langousis, E.I. Nikolopoulos, and E.N. Anagnostou (2022) The spatiotemporal evolution of rainfall extremes in a changing climate: A CONUS-wide assessment based on multifractal scaling arguments, Earth’s Future, 10 (3), e2021EF002539, doi: 10.1029/2021EF002539.
• Langousis, A., D. Veneziano, P. Furcolo, and C. Lepore (2009) Multifractal rainfall extremes: Theoretical analysis and practical estimation, Chaos, Solitons and Fractals, 39 (3), 1182–1194, doi: 10.1016/j.chaos.2007.06.004.
• Mearns, L.O., S. McGinnis, D. Korytina, R. Arritt, S. Biner, M. Bukovsky, et al. (2017) The NA-CORDEX dataset, version 1.0. NCAR Climate Data Gateway. Boulder (CO): The North American CORDEX Program, 10.

How to cite: Emmanouil, S., Langousis, A., Nikolopoulos, E. I., and Anagnostou, E. N.: A multifractal framework to evaluate extreme rainfall trends across scales under a changing climate, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 12–15 Oct 2021, Plinius17-1, https://doi.org/10.5194/egusphere-plinius17-1, 2021.

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Mediterranean hurricanes (Medicanes) are meso-scale cyclones typical of the Mediterranean area which during their lifetime may show some dynamical features with tropical cyclones: the presence of a quasi-cloud-free calm eye, spiral-like cloud bands elongated from the center, strong winds close to the vortex centre and a warm core. They are often associated to heavy rainfall and flooding, intense wind, and high waves and storm surge, and can be serious threats to human life and infrastructure. Recent studies highlighted that extra-tropical and tropical-like cyclone (TLC) characteristics can alternate or even coexist in the same cyclonic system, and that only in some cases strong diabatic forcing leads to tropical-like transition (i.e., purely barotropic structure) associated to shallow or deep warm core. In this study a comparative analysis among the Medicanes occurred during the Global Precipitation Measurement (GPM) era (i.e. since March 2014), is carried out. The goal is to extract common features from passive MW measurements to identify and characterize the transition to TLC phase during the Medicane evolution. Passive microwave measurements from the GPM constellation radiometers are used to characterize the precipitation structure and warm core properties throughout the Medicane evolution. In particular, the NASA/JAXA GPM Core Observatory (GPM-CO) active and passive microwave (MW) sensors are used in conjunction with ground-based LIghtning NETwork (LINET) measurements to analyse the rainband structure and infer microphysics processes and convection strength. On the other hand, MW temperature sounding channels available from AMSU-A and ATMS radiometers are used to identify the warm core and infer its properties (e.g., depth and symmetry) around the cyclone center.  The most intense Medicane on record, named Ianos, which swept across the Ionian Sea between 14 and 18 September 2020, is anlaysed in detail. The GPM-CO Dual-frequency Precipitation Radar (DPR) overpass, available for the first time during a medicane TLC phase, provides key measurements and products to analyze the 3D precipitation structure in the rainbands, offering further evidence of the main precipitation microphysics processes inferred from the passive MW measurement analysis. Moreover, the GPM-CO overpasses highlight a significant change in deep convection features between Ianos development and mature phases, which explain the substantial drop in lightning activity during Ianos TLC phase. The study demonstrates the value of satellite MW measurements in the GPM era to provide evidence of Medicanes' transition to TLC phase and to characterize its precipitation structure and microphysics processes.

How to cite: D'Adderio, L. P., Casella, D., Dietrich, S., Sanò, P., and Panegrossi, G.: Satellite-based characterization of Medicanes in the GPM era, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 12–15 Oct 2021, Plinius17-27, https://doi.org/10.5194/egusphere-plinius17-27, 2021.

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In recent years, the Mediterranean area has been affected by a continuous and significant increase in the intensity of violent weather events resulting in floods, hailstorms and tornadoes and an increasing impact on human activities, infrastructure and agricultural production.

Among these extreme events, a particularly intense phenomenon occurred on July 10, 2019 affecting much of the central Adriatic coast. In particular, the Pescara area was affected by a supercell that produced heavy rainfall and an exceptional hailstorm, with hailstones even larger than 10 cm in diameter, causing extensive damage.

This contribution documents, for the first time in Italy, the dynamics, morphology and main characteristics of the Pescara supercell [1] which was simultaneously observed, by two C-band meteorological radars of the national Department of Civil Protection (DPC). The results obtained highlight the irreplaceable role of dual-polarization Doppler weather radars in monitoring the evolution of hail, identifying the mesocyclone initiation and the related updraft and downdraft zones as well as their vertical extension, and highlighting the current limitations in determining the size of hail particles from radar measurements. Numerical simulations with the WRF model, using the HAILCAST module to simulate the evolution of hail, were carried out in order to evaluate the capabilities of an operational model in the simulation of such a particular event.

In the context of the intensification of extreme events, this work is also a food for thought on the main aspects to be addressed in the near future to improve the chain of alerting and modelling of extreme events for prevention and civil protection.

[1] M.Montopoli, E.Picciotti, L.Baldini, S.Di Fabio, F.S.Marzano, G.Vulpiani, "Gazing inside a giant-hail-bearing Mediterranean supercell by dual-polarization Doppler weather radar", Atmospheric Research,  Vol. 264, 15 Dec. 2021, 105852, https://www.sciencedirect.com/science/article/pii/S0169809521004087?dgcid=author

How to cite: Montopoli, M., Picciotti, E., Baldini, L., Di Fabio, S., Marzano, F., Miglietta, M. M., Tiesi, A., Mazzà, S., and Vulpiani, G.: Analysis of a hail bearing Mediterranean supercell through weather radars, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 12–15 Oct 2021, Plinius17-6, https://doi.org/10.5194/egusphere-plinius17-6, 2021.

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The scarcity of rainfall in the Sahara, the largest desert in the world, turns almost every rainstorm into an “extreme” event. The desert is situated to the south of the Mediterranean’s storm track and north of the equatorial-monsoonal rain belt, at the subsiding branch of both the Hadley and Walker circulation cells. The meager rainfall is observed by just a few rain gauges, recording few rainy days almost every year, occasionally triggering flash floods. Given the low amount of rainfall and the low number of observations, the characteristics of rainfall during such events were seldomly analyzed, especially at the scale of the whole Sahara. In this study, we (a) use high-resolution satellite remote sensing rainfall data (IMERG), to identify thousands of heavy precipitation events over the past 20 years, (b) characterize rainfall properties during these events, and (c) identify the governing atmospheric conditions on days of heavy precipitation using meteorological reanalysis (ERA5) data.

Heavy precipitation events occur throughout the Sahara, except for a small portion of its core. Southern Sahara events are the most frequent and happen mainly in summer. During winter, events occur primarily in the north and west parts of the desert. Preliminary analyses indicate that the events with the largest volume of rainfall (with volumes ≥ roughly the volume of Lake Chad) are characterized by much higher than normal upper-tropospheric temperatures over the eastern Mediterranean and lower temperatures over the southern Sahara.

The small number of events at each location is compensated in our analysis by the huge area of the desert with events occurring on average every second day. The high-resolution datasets we use enable us to characterize small-size events, with substantial implications at the local scale, which can help to cope with natural hazards.

How to cite: Armon, M., de-Vries, A., Marra, F., Peleg, N., and Wernli, H.: Heavy precipitation events where there’s no rain: Saharan rainfall climatology, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 12–15 Oct 2021, Plinius17-73, https://doi.org/10.5194/egusphere-plinius17-73, 2021.

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Over the last twenty years, remote monitoring of rainfall has become a fact. Thus, techniques to measure rainfall by analyzing satellite data is increasingly integrated in hydrology fields helping to tackle some of scientists’ biggest challenges such as the lack of rain gauges or the difficulty to access their data. 

This work is a study of the reliability and performance of precipitation observation products like PERSIANN-CCS (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System) with a temporal resolution of one hour (https://chrsdata.eng.uci.edu/) and like IMERG-GPMv6 (Integrated Multi-satellitE Retrievals for GPM version6) with a temporal resolution of 30 minutes (https://search.earthdata.nasa.gov/search) by using the programming language Python. These satellite-derived data are then compared to precipitation observed from rain gauges in the watershed Bouregreg-Chaouia in Morocco.   

The first procedure was to create a database of hourly rainfall collected from PERSIANN-CCS and IMERG-GPMv6 and based on measured rainfall events received from three rain gauges located in the study area. Afterwards, the comparison between the two data sources was executed through calculation of several statistical parameters such as the Pearson’s R correlation coefficient in addition to an analysis of the dimensionless values of rain (instantaneously observed precipitations from PERSIANN-CCS and IMERG-GPM).

Obtained results show a good correlation between values deduced from satellite imagery and those observed in rain gauges. Quantitively, the “R” correlation coefficients varied from 0.69 to 0.98 in the case of PERSIANN-CCS and from 0.86 to 0.99 in the case of IMERG-GPMv6. Furthermore, analysis of the dimensionless rainfall curves showed that they represent very comparable patterns, especially for the case of IMERG-GPMv6, it was also remarked that the latter dataset overestimated precipitation levels while the first underestimated them in comparison with ground station values. 

We concluded that, it’s possible to use instant rainfall data from satellites in contexts like hydrology for purposes like flood risk assessment. But, a correction of these products is necessary to improve the results and the quality of this data.

How to cite: EL Martili, I., Barkouki, K., Ahattab, J., and Serhir, N.: Comparison of instantaneous satellite rainfall data and observations from rain gauges network in the Bouregreg-Chaouia region in Morocco, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 12–15 Oct 2021, Plinius17-53, https://doi.org/10.5194/egusphere-plinius17-53, 2021.

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The use of non-conventional rainfall sensors can help to close the gap on rainfall characterization, which is one weak link in the modelling of the Earth’s water cycle. This has been an hot topic in hydro-meteorology for the last decade. In this frame, the EU COST ACTION named OPENSENSE (Opportunistic precipitation sensing network) has been recently approved and is running since October 2021 [1].

Specifically, the point-to-point wireless links massively used by the cellular networks for backhauling, namely, commercial microwave links (CML) have some unique features that render them attractive for rainfall detection [2]. The ubiquitous deployment of CML, the relatively high density of sensors, especially in urbanized areas, and the availability of raw data as outputs of the link quality control process are a strong plus. On the other hand, CML data are owned by mobile operators, hence they are not of public domain, and they are usually not optimized for rainfall measurements. It is therefore important to assess the capability of CMLs to detect the temporal and spatial patterns of precipitation and to quantify precipitation intensity by validation against conventional rainfall sensors where the latter are present and sufficiently dense [3].

In this work, we investigate the capability of CMLs to detect extreme rainfall events analyzing a case study in a large area North of Milan, where a mesh of more than 200 links is present. The region is covered by an operational network of rain gauges owned by ARPA Lombardia and by MeteoSwiss weather radar. Due to the different spatial sampling of CML, rain gauge and radar observations, specific procedures must be envisaged to carry out a fair data comparison. Even though individual CMLs may return large discrepancies in rainfall intensity values with respect to nearby rain gauges, especially in the case of short high-frequency links, it is possible to obtain a good reconstruction of the rainfall patterns of extreme events, without an in-advance calibration through ground truth data.

References:

[1] OPENSENSE COST ACTION official site, https://www.cost.eu/actions/CA20136/ (last accessed on May 2, 2022)

[2] Messer, H. Rainfall monitoring using cellular networks [in the spotlight]. IEEE Signal Processing Magazine 2007, 24, 144–142.

[3] Nebuloni, R.; Cazzaniga, G.; D’Amico, M.; Deidda, C.; De Michele, C. Comparison of CML Rainfall Data against Rain Gauges and Disdrometers in a Mountainous Environment. Sensors 2022, 22, 3218. https://doi.org/10.3390/s22093218

How to cite: Nebuloni, R., Cazzaniga, G., Deidda, C., D'Amico, M., and De Michele, C.: Detection of extreme rainfall events by a network of microwave links in the area of Milan, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 12–15 Oct 2021, Plinius17-38, https://doi.org/10.5194/egusphere-plinius17-38, 2021.

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Over the years, there has been an increase in extreme weather events which encouraged the scientific community to employ ever more different techniques for their studies. In this context, GNSS (Global Navigation Satellite System) find its place. Over the last thirty years, this technique has shown increasing applicability and reliability in the field of weather forecasting and analysis. However, there are points that it is critical to continue to investigate; one of the most discussed and noteworthy is the behavior of the GNSS-PWV (Precipitable Water Vapor from GNSS) time course during severe weather events. The relation between GNSS-PWV pattern and weather event evolution appears to be non-constant, sometimes showing a PWV peak at maximum convection, sometimes an advance and sometimes a delay. In this study we try to identify the causes of this unevenness of behavior using the number of lightning as a reference for the trend of convection and the VIL (Vertical Integrated Liquid content) obtained from radar as a term of comparison for the validation of GNSS-PWV.

How to cite: Mascitelli, A., Federico, S., Vulpiani, G., Crespi, M., and Dietrich, S.: GNSS-PWV time evolution in extreme weather events: comparison analysis with lightning and radar-VIL, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 12–15 Oct 2021, Plinius17-39, https://doi.org/10.5194/egusphere-plinius17-39, 2021.

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Lidar measurements can detect exceptionally light precipitation, such as drizzle or virga. This kind of precipitation is really hard to detect by other remote sensing techniques such as radars because a very short longwave (in the visible) is needed due to the small size of raindrops. For those reasons, lidar instruments are well suited to fill a gap in detecting light precipitation. In this study, we show the intercomparison results between the ground-based disdrometer observations and lidar precipitation algorithm detection at Goddard Space Flight center for future precipitation calibration/validation of the next European Space Agency (ESA) Earthcare mission, which is expected to be launched in 2023.

How to cite: Lolli, S., Lewis, J. R., Vivone, G., Sicard, M., Tokay, A., and Welton, E. J.: NASA MPLNET precipitation detection algorithm validation by ground-based disdrometers in the frame of future ESA Earthcare mission, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 12–15 Oct 2021, Plinius17-49, https://doi.org/10.5194/egusphere-plinius17-49, 2021.

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The WIVERN (WInd VElocity Radar Nephoscope, www.wivern.polito.it) mission, one of the four ESA Earth Explorer 11 mission candidates, currently in Phase-0, promises to complement the ADM-Eolus Doppler wind lidar measurements by globally observing, for the first time, vertical profiles of winds in cloudy areas. This work aims to determine the potential of the new cutting edge WIVERN W-band polarization-diversity Doppler radar for sampling Mediterranean hurricanes and monitoring their internal structure. It builds on the recently developed end to end simulator of the WIVERN dual-polarization Doppler conically scanning 94 GHz radar (Battaglia et al., Atmos. Meas. Tech., 15, 3011–3030, 2022, https://doi.org/10.5194/amt-15-3011-2022). The simulator is applied to: 1) the long-term CloudSat observation dataset of intense cyclones in the Mediterranean basin; 2) a Weather Research and Forecasting (WRF) Model very high horizontal resolution (333 m) run for Medicane Apollo occurred in October 2021. The analysis of the CloudSat results provides statistics for understanding which part of the cyclones can actually be seen by the W-band radar and where line of sight winds can be accurately measured. The high resolution WRF simulation provides insight into wind errors introduced by non-uniform beam filling and small-scale convective motions for the WIVERN observing system.

How to cite: Battaglia, A., Tridon, F., Parodi, A., Lagasio, M., Mazzarella, V., and Illingworth, A.: The Potential of the W-band polarization diversity Doppler radar envisaged for the WIVERN mission for looking into the internal structures of Mediterranean cyclones, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 12–15 Oct 2021, Plinius17-74, https://doi.org/10.5194/egusphere-plinius17-74, 2021.

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How to cite: Husson, R., Mouche, A., Archer, O., Berger, H., Colin, A., Peureux, C., and Goimard, G.: Combined high-resolution rain/wind measurements over extreme wind events using Synthetic Aperture Radar , 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 12–15 Oct 2021, Plinius17-81, https://doi.org/10.5194/egusphere-plinius17-81, 2021.

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Provided that the population living in cities is increasing, projected to reach 5.2 billion in 2030, and that heat waves are getting more intense and lasting as a consequence of the global warming, the urban heat island (UHI) phenomenon is leading increasingly to extremely high temperatures within cities. It is therefore important to find reliable and simple methods for estimating and characterizing at a high resolution the UHI.

In this work we characterize the urban heat island (UHI) of Rome, Italy, during summer, through a dense weather station network. Measurements were collected in summers 2019-2020. We calculate the UHI intensity using a method that relates the air temperature to imperviousness (IMP), which quantifies the presence of artificially sealed surface in a radius around each station using Copernicus Land Monitoring Service satellite data. To assess the reliability of this method we made a comparison with the LCZ-based approach, finding compatible daily trends of UHI intensity, with a fixed bias during night. Our method both simplifies the measurement area classification and allows to determine the UHI intensity even when measurements in totally urban and totally rural areas are not available. The correlation coefficient values between IMP and daily maximum, minimum and mean temperatures were 0.17, 0.81 and 0.82, respectively, evidencing the nighttime UHI peak observed in other cities. The UHI intensity diurnal cycle pattern showed, starting from its minimum of -0.1°C at 10:00 (CET), a progressive increase which intensifies after sunset, reaching a maximum of 3.4°C at midnight. During the night a slight decrease is observed, which exacerbates after sunrise. We did not find a relevant correlation between UHI and heat waves.

How to cite: Cecilia, A., Casasanta, G., Petenko, I., Conidi, A., and Argentini, S.: Measuring the urban heat island of Rome through a dense weather station network and imperviousness Copernicus Land Monitoring Service data, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 12–15 Oct 2021, Plinius17-52, https://doi.org/10.5194/egusphere-plinius17-52, 2021.

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About 10000 hectares of forest, corresponding to the 12% of the national forestry heritage, are lost each year in Italy due to arson or negligent fires. Consequences on ecosystem and natural equilibrium are relevant, since the time for the natural restoration process may take several decades. Climate extremes exacerbates Mediterranean area fire risk, due to prolonged drought conditions. On the other hand, hydrogeological risk is also expected to increase over burnt slopes, where surface runoff is incremented due vegetation loss. According to the current legislation, fire risk management is in charge of the Italian Regional Civil Protection, therefore the development of user-oriented tools, able to prevent the fire hazardous conditions, is key element to ensure the forest-fire risk management. In the proposed model, the atmospheric conditions preceding a forest fire are estimated thought the combination of air temperature and relative humidity, as reference of atmospheric parameters.The approach assesses how many times the observed air temperature and RH of the previous 12 days area above the critical conditions (i.e., >25°C and < 50%, respectively). The model validation is carried out by using a three-years dataset of forest fires, that hit the Abruzzo region from 2018 to 2020, combined with meteorological data from civil protection gauges’ network. The developed index identified fire-precursors in the 80% of selected case studies. The missing 20% is manly related to the meteorological uncertainty in poorly gauged areas. Starting from the index validation, a pre-operational tool forced with ECMWF analyses is also described.

How to cite: Lombardi, A., Pizzi, G., Colaiuda, V., Ferrante, F., Tuccella, P., Di Antonio, L., Lidori, R., Di Fazio, D., Malatesta, T., Costa Saura, J. M., Spano, D., Rizi, V., Marzano, F. S., Luigi Rossi, F., Liberatore, S., Casinghini, M., Rossi, G., and Tomassetti, B.: Atmospheric Precursor of fire hazard: development of a fire-sentinel index for risk management in Abruzzo Region (Central Italy)., 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 12–15 Oct 2021, Plinius17-57, https://doi.org/10.5194/egusphere-plinius17-57, 2021.

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Mediterranean European countries are considered fire-prone regions, being affected by fire events every summer, and Portugal is among these countries. Moreover, Portugal has been recording large burned areas over the last 20 years. Catastrophic fire season occurrence, associated with hot and dry conditions and high fuel availability in forests, has been recurrently destroying several ecosystems. Furthermore, the Mediterranean basin has been stated with high potential to be one of the most disturbed areas due to climate change, which strongly promotes the increase of fire weather conditions and fire risk and, thereby, the occurrence of more extreme fire seasons.

During the last years, Portugal has been implementing new effective policies regarding the prevention of fires during pre-fire season months, improving the investment in combat strategies. In this context, our study contributes to identify the regions with more potential to burn in a specific fire season. Through satellite-based data and reanalysis products, with large temporal extent and moderate to high spatial resolution, we combine a wide range of variables linked, directly or indirectly, with fire, in order to identify the most exposed regions to burn.

The application of Principal Component Analysis (PCA) to our range of climatological, ecological and biophysical parameters allowed to assess six different regions with more susceptibility to fire events. The central and the southernmost regions of the country presented a stronger signal on PCA analysis, indicating a higher exposure to future fire events. Fuel accumulation during several months, in conjunction with topography, land cover and fire weather conditions were the terms that explained the most variability of the first six PCAs. Therefore, with these results, our work addresses the key trigger parameters of fires, and the most susceptible areas to burn in Portugal, contributing to enhancing the effectiveness of fire prevention policies.

Acknowledgements: This study was supported by FCT (Fundação para a Ciência e Tecnologia, Portugal) through national funds (PIDDAC) – UIDB/50019/2020, and under the projects FlorestaLimpa (PCIF/MOG/0161/2019) and FIRECAST (PCIF/GRF/0204/2017).      

How to cite: Páscoa, P., Ermitão, T., and M. Gouveia, C.: Identification of the most fire susceptible areas in Portugal , 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 12–15 Oct 2021, Plinius17-76, https://doi.org/10.5194/egusphere-plinius17-76, 2021.

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The damages generated by fire events on vegetation structure and its evolution and the economic impacts on human activity, life and infrastructures have led the scientific interest to develop tools and algorithms able to support the detection and monitoring of burned areas (BAs).

The possibility of monitoring the fire evolution and mapping the BAs has been strongly promoted in last decades by the opportunity to use a significant quantity of satellite observations. Earth observation (EO) data represent one of the key components in supporting both government agencies and local decision-makers in monitoring natural disasters such as wildfires. Among EO instruments, multispectral sensors have demonstrated their suitability for BA mapping, because fire has significant effects on vegetation reflectance. The Copernicus Sentinel-2 (S2) with 20-m spatial resolution and a 5-day return period is a good candidate for near real-time (NRT) monitoring of the fire situation throughout the fire season.

Pulvirenti et al. (2020) proposed an automatic NRT BA mapping approach based on S2 data. They developed the AUTOmatic Burned Areas Mapper (AUTOBAM) tool to respond the need of the Italian Department of Civil Protection in monitoring spatial distribution and numerousness of the BAs during the fire season (June- September) over the Italian territory. It is used, in pre-operational mode, since summer 2019. The atmospherically corrected Level-2A(L2A) surface reflectance products from S2 are used by AUTOBAM: the automatic chain downloads and processes the most updated L2A products available on Copernicus Open Access Hub over the studied area. Then, a change detection approach is applied to the three spectral indices chosen to map BA (Normalized Burn Ratio, the Normalized Burned Ratio 2, and the Mid-Infrared Burned Index). AUTOBAM compares the values of these indices acquired at current time with the values derived from the most recent cloud-free S2 data. The procedure for BA mapping is based on different sequential image processing techniques such as clustering, automatic thresholding, region growing that conduce to a final BA map with grid pixel size of 20m. Finally, a quality flag is included for each AUTOMAB BA to certify a temporal and spatial correspondence with ancillary data, such as active fire products derived from MODIS and VIIRS, as well as national fire notifications.

This processing chain has been tested for the fire seasons of years 2019-2021, and the AUTOBAM-derived BAs have been compared with the burned perimeters compiled by Carabinieri Command of Units for Forestry, Environmental and Agri-food protection. A validation procedure in fact has been realized to verify a-posteriori the ability of AUTOBAM to detect the actual BAs mapped by Carabinieri after local surveys. Timing and spatial criteria are adopted to validate AUTOBAM mapping, and a threshold of 20% overlapping is fixed to make an AUTOMBAM BA classified as a reliable detection. Results indicate that the proposed method has potential for NRT mapping of BAs.

How to cite: Fiori, E., Squicciarino, G., and Pulvirenti, L.: An automatic algorithm for near real-time burned area mapping from Sentinel-2 data: validation results for 2019-2021 fire seasons over Italy, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 12–15 Oct 2021, Plinius17-43, https://doi.org/10.5194/egusphere-plinius17-43, 2021.

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Coastal areas are increasingly becoming more vulnerable due to economic overexploitation and pollution. The Italian Space Agency (ASI) supports the research and development of technologies aimed at the use of multi-mission EO data, in particular of the national COSMO-SkyMed Synthetic Aperture Radar and PRISMA hyperspectral missions, as well as Copernicus Sentinels, through the development of algorithms and processing methodologies in order to generate products and services for coastal risk management.

In this context, ASI has promoted the development of the thematic platform costeLAB as a tool dedicated to monitoring, management and study of coastal areas (sea and land). This platform was developed in the frame of the “Progetto Premiale Rischi Naturali Indotti dalle Attività Umana - COSTE", n. 2017-I-E.0 (http://costelab.asi.it/en/homepage-en/), funded by the Italian Ministry of University and Research (MUR), coordinated by ASI and developed by e-GEOS and Planetek Italia with the participation of National Research Council of Italy (CNR), Meteorological Environmental Earth Observation (MEEO) and Geophysical Applications Processing (G.A.P.) s.r.l. The aim of the project was to define, develop and run in a pre-operational context, an integrated system that exploits Earth Observation data to support the management of coastal areas environmental processes and risks. The platform is addressed to the institutional, scientific and industrial users and allows the study, experimentation and demonstration of new downstream pre-operational services for the monitoring of the coastal area environment and in support to risk management.

The costeLAB platform provides a common entry point for several web-based EO data processing in the field of coastal zone monitoring and emergency management, to generate and visualize products by means of consolidated algorithms that users can utilize for their duty tasks.

The rationale of the platform is to “keep applications close to the data”, i.e. allowing users to access huge amount of EO data relieving them of demanding tasks for big data download and processing in local computers. Users are therefore able to generate reliable products by means of validated algorithms with reduced processing times.

Of the thirty consolidated products that users can generate through the platform (Candela et al., 2021), the paper will showcase in particular those of main relevance for coastal risk management: Coastline change map, Coastal subsidence rate, Landslide activities, Hydrocarbon beaching, Flooding maps, Flood exposure, Erosion exposure, Coastal pollution at national scale, Pollution at coastal scale, under different application scenarios.

Finally, the paper will present experimental scientific products that Researcher Users from CNR generated over selected Mediterranean sites via testing the “collaborative virtual laboratory” namely “Virtual Lab”, i.e. the ad hoc costeLAB facility for researchers and developers to share, test and demonstrate innovative algorithms in order to build new processing chains. These experiments within the platform followed on from dedicated research activities that were carried out on the various components of the marine-coastal environment (land-sea interface) during the costeLAB project. The breadth and novelty of these activities towards an improved understanding of Mediterranean coastal hazards will be presented.

How to cite: Candela, L., Coletta, A., Daraio, M. G., Lopinto, E., Tapete, D., Palandri, M., Pellegrino, D., Zavagli, M., Amodio, A., Vecoli, A., Mantovani, S., and Giardino, C.: costeLAB platform: a prototype collaborative environment for research and applications in support to coastal risk management, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 12–15 Oct 2021, Plinius17-71, https://doi.org/10.5194/egusphere-plinius17-71, 2021.

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Earth Observation (EO) data characterised by a spatial resolution in the range of 10-30 m (e.g., Sentinel 1 – S1, Sentinel 2 – S2, Landsat series), systematically acquired and freely distributed by national and international space agencies/institutions (e.g., ESA, EU, NASA), are a valuable tool for analysing shoreline evolution trends. These data can be used for supporting coastal erosion hazard and risk management strategies (Cenci et al., 2018). However, the accuracy of such trends is not often quantified because of the difficulties in finding systematic and freely available EO data at Very High Resolution (VHR) concurrently acquired over the same target areas to use as reference.

Within this context, this work was conceived for taking advantage of the Copernicus VHR optical datasets (spatial resolution: 2-4 m) to use as reference data to validate the shoreline evolution trends obtained by exploiting S1 and S2 images. The abovementioned analysis was carried out for a short-term scenario (i.e., 3 years: from 2015 to 2018) in an exemplifying littoral of the Mediterranean Sea characterised by both urbanised and natural coastal areas: i.e., Lido di Ostia (Rome, Italy). Importantly, the shoreline extraction method used in this case study was based on a methodological approach that allowed to map the shoreline positions with sub-pixel precision (Bishop-Taylor et al., 2019; Cenci et al., 2021).

Preliminary results showed that the shoreline evolution trends based on the S2 Visible Near-InfraRed (VNIR) spectral bands (spatial resolution: 10 m) retain an accuracy of 4.5 m (in term of Root Mean Squared Error - RMSE), if compared against the corresponding trends acquired by using Copernicus VHR data with a spatial resolution of 2 m. At the conference, the results of the analysis based on S1 data will be also presented, as well as a thorough interpretation and discussion of the S1 and S2 -based results that take into account the characteristics of the coastal area under assessment (e.g., presence or absence of defence structures) and the relationship between the magnitude of the shoreline advance/retreat trends and the corresponding accuracy. The overall objective of this work is to show the potentialities of the Copernicus EO data for the management of the coastal erosion hazard/risk in the Mediterranean area.

References:

• Bishop-Taylor R., Sagar S., Lymburner L., Alam I. and Sixsmith J. Sub-Pixel Waterline Extraction: Characterising Accuracy and Sensitivity to Indices and Spectra. Remote Sensing. 2019; 11(24):2984. https://doi.org/10.3390/rs11242984
• Cenci L., Disperati L., Persichillo M.G., Oliveira E.R., Alves F.L. and Michael Phillips. Integrating remote sensing and GIS techniques for monitoring and modeling shoreline evolution to support coastal risk management. GIScience & Remote Sensing. 2018. 55(3), pp. 355-375.https://doi.org/10.1080/15481603.2017.1376370
• Cenci L., Pampanoni V., Laneve G., Santella C. and Boccia V. Evaluating the Potentialities of Copernicus Very High Resolution (VHR) Optical Datasets for Assessing the Shoreline Erosion Hazard in Microtidal Environments. AIT Series: Trends in earth observation. 2021. Volume 2, pp. 81-84. ISSN: 2612-7148. ISBN: 978-88-944687-0-0. Published on behalf of the Associazione Italiana di Telerilevamento (AIT) https://aitonline.org/wp-content/uploads/2021/10/PlanetCarefromSpace.pdf DOI: 10.978.88944687/00

How to cite: Cenci, L., Pampanoni, V., Laneve, G., Santella, C., Boccia, V., and Albinet, C.: Assessing the Accuracy of Shoreline Evolution Trends Obtained by Using Copernicus Earth Observation Data. Case Study: Mediterranean Coastal Areas, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 12–15 Oct 2021, Plinius17-23, https://doi.org/10.5194/egusphere-plinius17-23, 2021.

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Surface displacement is one of the main parameters to assess the natural hazard in volcanic and seismic regions, as well as in areas affected by landslides and subsidence.

Differential Synthetic Aperture Radar Interferometry (DInSAR) is becoming one of the key techniques to measure ground deformation in any atmospheric conditions, with continuous day and night imaging capabilities and a high accuracy level, thanks to its capability to provide dense measurements at large spatial scale and at relatively low cost.

The increasing diffusion of the use of DInSAR is also due to the large availability of huge and easily accessible SAR data archives, as those acquired, since late 2014, by the Copernicus Sentinel-1 constellation, which is globally and routinely providing C-band SAR data with a defined repeat-pass frequency. Therefore, with such a constant and reliable availability of data, it is possible to use the DInSAR technique for monitoring purposes, such as those related to the measurements of ground motion in natural hazard prone areas.

In this work, we present the operative services and tools that have been developed at CNR-IREA, in the framework of its cooperation with the Italian Department of Civil Protection (DPC), for detecting and monitoring large scale surface deformation through the use of the DInSAR technique.

A first service is focused on seismic areas and relies on the publicly accessible earthquake catalogues. Once an earthquake that likely produces ground deformation occurs, it triggers an automatic DInSAR processing that generates the co-seismic induced displacement maps, by retrieving the relevant pre- and post-seismic Sentinel-1 acquisitions. While being focused on the Mediterranean region the system works at global scale.

A second service is devoted to volcano displacement monitoring. The designed system is fully automatic and the process is triggered by the availability, for every monitored volcano site, of a new SAR data in the Sentinel-1 catalogues acquired from both ascending and descending passes. The data, per each orbit, are automatically ingested and then processed through the well-known Parallel Small BAseline Subset (P-SBAS) DInSAR technique that allows generating the corresponding displacement time series and mean displacement velocity maps. The so-retrieved Line of Sight (LOS) measurements are then combined to compute the Vertical and East-West components of the deformation, which are straightforward understandable by the end user. This service is currently operative for the main active Italian volcanoes (Campi Flegrei caldera, Mt. Vesuvius, Ischia, Mt. Etna, Stromboli and Vulcano), but it can be easily extended to include other volcanic areas on Earth.

Finally, a third tool is based on the use of an airborne platform which is equipped with a X-band and L-band SAR sensor, and that is used in conjunction with the already mentioned systems to provide further information on the areas under study.

Retrieved deformation results and their implication in the understanding of the analyzed phenomena will be discussed at the conference.

This work is supported by the CNR-IREA and Italian DPC agreement, the CNR-IREA/MiTE-DGISSEG agreement, the H2020 EPOS-SP (GA 871121), the ASI DInSAR-3M project, and the I-AMICA (PONa3_00363) project.

How to cite: Casu, F., Berardino, P., Bonano, M., Buonanno, S., Casamento, F., De Luca, C., Esposito, C., Fusco, A., Lanari, R., Manunta, M., Manzo, M., Monterroso, F., Natale, A., Onorato, G., Perna, S., Roa, Y., Striano, P., Yasir, M., Zeni, G., and Zinno, I.: DInSAR-based monitoring services for ground deformation retrieval on active volcanoes and seismic regions through spaceborne and airborne radar sensors, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 12–15 Oct 2021, Plinius17-78, https://doi.org/10.5194/egusphere-plinius17-78, 2021.

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Earth Observation (EO) data plays an important role in understanding how climate change impacts our environment. However, when considering the ensuing disaster as the result of heavy precipitation for instance, we observe that anthropogenic contributions such as urbanisation and land use change contribute significantly to the risk of a hazard influenced by external factors becoming a disaster (man-made disaster).

The H2020 EOPEN Project (https://eopen-project.eu/) demonstrated possibilities to fuse Sentinel data with multiple, heterogeneous, and big data sources, to improve the monitoring and analysis capabilities of the future EO downstream sector2. Additionally, the involvement of mature ICT solutions in the EO sector shall address major challenges in effectively handling and disseminating Copernicus-related information to the wider user community. A reasonable level of automation was achieved making it possible to establish workflows to implement systematic processing of multiple data sources.

EOPEN3 components are a framework core, a Dashboard environment, application specific extensions and three Pilot Use Cases which demonstrate its usage focused, respectively, on flood risk assessment and prevention, food security and climate change; moreover, the Crop Water Demand module implemented in the H2020 MOSES4 was run through the platform to demonstrate its interoperability.

Some achievements with regards to Mediterranean natural risks are:

PUC1 - Flood risk assessment and prevention - in this use case stakeholders, from offices, from local scale (municipality of Vicenza) to government scale, with specific roles during flood emergencies, have been involved to specify the needed information elements and presentation features to support their current operations; also, the early warning system (EWS) Flood Forecasting System to predict water level of the Bacchiglione river in Vicenza, implemented by the Eastern Alps River Basin District Authority (AAWA), was empowered through access to several additional input data for their hydrological model, such as those available from Copernicus Global Land Services (CGLS) as well as an additional weather forecast, provided by the Finnish Meteorological Service, and maps of the flooded areas generated in the platform.

PUC3 - Climate Change - this use case focused on challenges that climate change brings to the local reindeer herding livelihoods and to the infrastructure and transportation in Finland, which can be a reference for Mediterranean countries facing similar problems in mountainous areas.

While EOPEN achieved a level of processing autonomy, not all aspects of the operational workflow were included. Adding interconnection and feedback mechanisms would significantly reduce human intervention needed to compliment the data and connect the systems that eventually lead to delivering the service in support of decision makers, also interfacing currently used DSS. For example, in the case of PUC1, the system supported the preparedness and partly the response (weather forecast included) phases whereas recovery and prevention actions were not included.

Anticipating future Horizon calls, future EOPEN improvements will address the quality of modelling in particular risk assessment and compounding cascading events, and the connectivity of the various steps of operational workflows thus reducing the need for human intervention simply to create a continuum of the workflow to deliver services.

How to cite: Gale, L. and Scarpino, G.: Federated platforms in support of risk assessment and cascading effects: EOPEN1 - one step done, still more to go , 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 12–15 Oct 2021, Plinius17-98, https://doi.org/10.5194/egusphere-plinius17-98, 2021.

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The susceptibility (S) of cloud radiative effect (CRE) to aerosols is approximated by satellite retrieval of the fractional change of CRE to a similar fractional change of ln(N_d), where N_d is the cloud drop number concentration [cm^-3]. Larger S means larger aerosol cloud-mediated cooling effect with increasing aerosols that can serve as cloud drop condensation nuclei. The full record (2003-2021) of MODIS satellite observations was used to retrieve N_d, cloud fraction (CF), albedo (A) and CRE of boundary layer water clouds over all the world oceans. The susceptibility of CRE over the Mediterranean Sea is found to be exceptionally small compared to the oceans at the same latitude band. The causes for that are:

• Small albedo susceptibility. It is caused by the large background of N_d, which is more than 200 cm^-3 on average – 3 times compared to the oceans at the same latitude band.
• Small cloud fraction susceptibility especially at the Eastern Mediterranean. It is also caused by the large background of N_d, which suppresses rainfall from shallow clouds that break them up.
• Small occurrences of events of low clouds – less than half compared to the oceans at the same latitude band.
• The occurrence of low clouds is only 1/3 of the occurrence over the oceans at the same latitude band.

The CRE susceptibility is the sum of the already small albedo and CF susceptibilities.

The total aerosol cloud-mediated cooling is very small because it is proportional to the CRE susceptibility multiplied by the very small occurrence of low clouds over the Mediterranean.

The probable root cause for all of this is the smallness of the Mediterranean Sea, which is dominant by advection of dry and polluted air from the adjacent continents all around it.

How to cite: Rosenfeld, D. and Cao, Y.: Exceptionally low susceptibility of aerosol cloud-mediated radiative forcing over the Mediterranean Sea, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 12–15 Oct 2021, Plinius17-99, https://doi.org/10.5194/egusphere-plinius17-99, 2021.

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Increasing extreme precipitation intensity at short duration is reported in recent literature and related to the global warming. For improving risk management and adaptation to changing climate, it is important to estimate the changes in hourly extremes, because they cause numerous hydro-geological hazards. High resolution climate models (Convection-permitting models, CPMs) resolve the scales at which convective processes occur, and can provide higher confidence in the future estimates of hourly precipitation than coarser resolution models. However, since actual CPM runs are available for short time slices (10–20 years), estimation of extremes by using classical Extreme Value approaches is difficult. Novel methods based on the concept of ordinary event have shown the capacity of deriving reliable frequency analyses from short data records, and they can be successfully applied to CPMs.

Recent literature reported distinct orographic effects on precipitation extremes. In particular, decreasing intensity with elevation for hourly extremes is found (“reverse orographic effect”) as contrasted with the orographic enhancement of precipitation for long durations. The reverse orographic effect was tentatively associated to orography-induced turbulence. These processes could be sub-grid even for CPMs, so it is crucial to understand whether and how CPMs can represent the orographic effect before using the simulations to project future extremes in mountainous areas.

We focus our study on an orographically complex area in the Eastern Italian Alps. Precipitation data comes from: i) ~170 5-min resolution rain gauges (our benchmark), ii) CPM simulations from COSMO model, run at 2.2 km spatial resolution and 1h time-resolution. The model is driven with ERA Interim re-analyses for the period 2000-2009. A storm-based statistical method is applied to both observed and simulated time series, and we use a Weibull distribution for modelling the upper tail of ordinary events. We derive the distribution parameters and extreme return levels up to 20-year return period for durations between 1 and 24 h. We look at their dependence on elevation, and we quantify the bias between observations and CPM, the dependence of the biases with elevation.

Spatial patterns in the CPM biases on the annual maxima and the modelled return levels emerge for short durations, while a general better agreement between model and observation is found at the daily duration. For the 1h return levels, the bias depends on elevation, with increasing overestimation with elevation, which implies a weak representation of the reverse orographic effect.

This work shows that we can have reliable estimates of high return levels from short CPM runs by using proper statistical methods. The results can improve our understanding of the changes in the meteorological processes underlying the changes in the precipitation extremes, and could help us develop adjustment approaches accounting for the role of orography at multiple durations.

How to cite: Dallan, E., Marra, F., Fosser, G., Formetta, G., Marani, M., Schaer, C., and Borga, M.: How is the reverse orographic effect on hourly extreme precipitation reproduced by a high resolution climate model?, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 12–15 Oct 2021, Plinius17-66, https://doi.org/10.5194/egusphere-plinius17-66, 2021.

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The RESILIENCE project aims at developing  an integrated methodology for assessing the impact of climatic variations and changes on the intense precipitation and wind regimes, and on the consequent triggering of flash floods, debris-flows and wind-related forest damages. A significant increase of short and intense precipitation is expected in the next future due to global warming, with consequent impacts on flash floods and hydro-geomorphic hazards such as shallow landslides and debris flows. Despite their societal importance, only few studies have explored potential climate change effects on these hydrological and hydro-geological processes. In fact, no accepted estimates of such changes to be used in engineering practice or environmental management planning exist so far, nationally or regionally.

The RESILIENCE project tries to address this specific knowledge gap. Two recent scientific advances are at the basis of the development of RESILIENCE. The first advance is the advent of high-resolution climate models, also called Convection-Permitting Climate Models (CPM), which improve the representation of both precipitation and wind field at the sub-daily scales compared to the standard coarser resolution Regional Climate Models. However, due to their computational costs, simulations are currently available for only short (typically ten years) time slices and few emission scenarios. These time series are too short to provide reliable statistics of extremes if analyzed using the classical extreme value methods. A second recent advance in the field of extreme value theory, the Metastatistical Extreme Value Distribution (MEVD), allows to overcome this limitation: it provides reliable extreme event probability estimates even from short time series, as in the case of CPM outputs, since it is based on all “ordinary events'' in the series instead of just yearly maxima or a few “peak-over-threshold” values per year as in the traditional methods.

Given this background, and focusing on the Veneto region in Italy as a study area, the specific objectives of RESILIENCE are 1) to quantify near (2041-2050) and far (2090-2099) future changes in precipitation and wind extremes probability at sub-daily temporal scales with respect to the baseline (1996-2005) using the MEVD approach  and high-resolution COSMO-CLM simulations, 2) to quantify the associated future impacts on flash floods, debris flows and forest damages, 3) to provide data and hazard models to support flood and forest risk management plans in the Italian North-East accounting for future climate changes.

RESILIENCE brings together an interdisciplinary group of scientists, from hydrologists, to climate modelers, to statisticians, to forest science experts, and is based on the interaction with three key Project Stakeholders. The project results will be communicated and disseminated to a wide audience of residents in the Veneto region and beyond, through collaborations with Museums, Academies and Local Authorities.

How to cite: Dallan, E., Borga, M., Marra, F., Fosser, G., Martina, M., Marani, M., Gregoretti, C., Lingua, E., Canale, A., Massimiliano, M., Bernard, M., Costa, M., Cesarini, L., Dalmasso, G., Caruso, M. F., Zanaga, V., and Zaramella, M.: RESILIENCE Project - Extreme Storms in the Italian North-East: frequency, impacts and projected changes, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 12–15 Oct 2021, Plinius17-84, https://doi.org/10.5194/egusphere-plinius17-84, 2021.

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We investigate the spatial and temporal patterns of annual and seasonal biases in extreme precipitation simulated by a convection permitting climate model forced with reanalysis data (Era Interim driven COSMO-CLM model) across a 10-years period (2000-2009). Specifically, we aim at developing an adjustment procedure able to preserve extremes at different temporal and spatial scales, and which can be applied to future scenarios.

The biases are here defined as the ratio between simulated and observed rainfall at 130 rain gauges. The quantile-based analysis reveals a general overestimation for gauges located in foothill or mountain areas (elevation > 500 m asl), and a general underestimation over lowland sites. This behavior is recurrent for various investigated quantities, such as annual or seasonal biases, and their counterparts estimated upon Extreme precipitation Values (EV) or wet periods. We also observe a temporal heterogeneity of the biases estimated in different years or seasons. Dry years (e.g. 2003) are characterized by remarkably high biases, while those estimated upon springs and autumns data within the investigation period are generally overestimated and underestimated, respectively.

We explore two preliminary adjustment approaches: Quantile Mapping (QM) and Linear Scaling (LS) adjustments. QM corrects simulated rainfall series but can affect the rainfall temporal autocorrelation. Conversely, LS preserves the autocorrelation but fails in the correction of seasonal and annual biases. EV-related biases are not properly corrected, and further statistical methods need to be formulated to correct EV simulated rainfall while both respecting their ACF and taking into account orographic effects.

How to cite: Schiavo, M., Dallan, E., Fosser, G., Marra, F., and Borga, M.: Statistical methodologies for biases correction of precipitation for a convection-permitting climate model and their spatio-temporal patterns in North-Eastern Italy, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 12–15 Oct 2021, Plinius17-88, https://doi.org/10.5194/egusphere-plinius17-88, 2021.

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Liguria region is historically affected by severe hydro-meteorological events often resulting in dramatic death tolls and large socio-economic impacts. On 7-8 October 1970, Genoa, region capital city, was struck by the most catastrophic flood event of its history. On the evening of 7 October pre-frontal storms affected the western side of the city (Voltri, Prà and Pegli municipalities), while on 8 October 1970 an anticyclone block generated recurring convective systems that hit Genoa city and above all the Bisagno Valley. The heavy rainfall continued more than 24 h with highs at Bolzaneto rain gauge (Polcevera Valley, northwest of Genoa city center) where over 950 mm of rainfall in 24 hours was measured. Over the city center and the Bisagno Valley, 400 mm in 24 h was recorded. The Bisagno stream channels overflowed, submerging the city center. The 1970 event in Genoa City was also the most dramatic in terms of damage: 44 fatalities occurred and over 2000 individuals were evacuated.

This study hindcasts the meteorological evolution of this event at high spatial resolution (1.5 km) and temporal one (1 hour) using the Weather and Research Forecasting (WRF) model by downscaling the ERA5 climatology developed by European Center for Medium-Range Weather Forecast (ECMWF). The weather hindcast scenario is compared with available meteorological observations as well as with recorded geomorphological impacts on Genoa city center and municipalities.

How to cite: Parodi, A., Boni, G., Faccini, F., and Paliaga, G.: Hindcast high-resolution simulation of the most catastrophic rainfall event in Genoa City (7-8 October 1970): hydro-meteorological and geomorphological analysis, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 12–15 Oct 2021, Plinius17-89, https://doi.org/10.5194/egusphere-plinius17-89, 2021.

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Changes in slope stability can arise from hydro-mechanical processes driven by atmosphere-soil interaction, and these processes are affected by the temperature at which they occur. This is well studied in cold climates, but even at temperatures well above freezing, experiments show significant changes in soil parameters upon comparatively small variations in temperature. These effects are typically neglected in geomechanical models, as their formulations do not typically include temperature or, if they do, they relate it to soil hydrology and not soil mechanics. Therefore, by only focusing on extremes in hydrological forcing, we may be underestimating the role of climate change in landsliding in temperate regions. Within ongoing projects, we are exploring the relationship between temperature and slope stability with various approaches and at various scales. In the laboratory, we are conducting temperature-controlled oedometer tests and ring-shear tests on saturated soils, observing patterns of strengthening or weakening in relation to both the mineralogy and shear rate. We also are evaluating correlations between basic and mechanical properties on the basis of the soil’s response to heating and cooling. We are using such correlations in the field to obtain insights on slope stability, particularly of rock bodies. Focusing on soils, we are developing thermo-hydro-mechanical model formulations for slope stability under climate change. At the catchment scale, we are using statistical tools to find whether a temperature-related variable (such as the land surface temperature) can inform landslide susceptibility models. Insights from debris flow-yielding steep mountain catchments and gentle clay slopes with slow creep processes suggest the significance of temperature and its fluctuations in influencing/controlling gravitational processes also independently of its influence on vegetation and hydrological forcing.

How to cite: Scaringi, G., Loche, M., Tourchi, S., and Lombardo, L.: Temperature and slope stability in temperate climate, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 12–15 Oct 2021, Plinius17-26, https://doi.org/10.5194/egusphere-plinius17-26, 2021.

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Quantifying rainfall volumes at varying duration and frequencies (e.g. design rainfall) and their uncertainty is crucial for a reliable design of water related infrastructures, such as flood retention reservoirs, urban drainage systems, spillways, culverts. This is of particular relevance in orographically complex area where extreme rainfall could trigger hydro-geological hazards.

Estimate of the design rainfall and its uncertainty is usually done at-site, i.e. at the position where the rain gauge is located and regionalization methods are required to provide estimates in ungauged locations. 

In this work we exploit the potential of the Simplified Metastatistical Extreme Value (SMEV) statistical framework for the analysis of extreme rainfall based on ordinary events and not only the annual maxima and we evaluated the performances of two different regionalization methods (namely, regionalization of extreme rainfall quantiles and of the distribution function parameters). The performance of the two selected approaches is evaluated by leave one out cross-validation and traditional goodness of fit measures (i.e. percent bias, percent root mean square error, and Kling Gupta efficiency).

The study area is the Alto Adige Region located in the Italian Alps, where 57 rain gauges at sub-hourly and hourly time steps are analyzed.

Preliminary results show that accounting for elevation in the regionalization (Kriging) methods provides better performances and reduce the design rainfall uncertainty in ungauged locations.

How to cite: Formetta, G., Marra, F., Dallan, E., and Borga, M.: Extreme rainfall estimation in orographically complex ungauged locations, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 12–15 Oct 2021, Plinius17-80, https://doi.org/10.5194/egusphere-plinius17-80, 2021.

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This work analyses the spatial structure of some extra-ordinary extreme rainfall events (EEEs) in Liguria (NW of Italy). The EEEs affecting the region are often caused by Mediterranean Back-building MCS events which are usually characterized by a very small spatial extent. EEEs produce the annual maximums of precipitation for short durations, commonly used for the probabilistic analysis of rainfall and flood hazard.

The characteristic spatial scale of the EEE analyzed, represented by the cross-sectional dimension of the peak structures, compared with the average rain gauge density shows that the former is often less than or of the same order as the latter.

Rain gauge data are used to obtain statistics of extreme rainfall, usually expressed by rainfall depth-duration-frequency (DDF) curves. This statistical approach relies on the assumption that the maxima observed by the raingauges are matching with the local maxima of the actual event. The lower is the average rain gauge density compared to the characteristic spatial scale of EEEs, the less valid is the aforementioned hypothesis.

The spatial analysis of some recent EEEs in the region underlines that the mismatch between the characteristic spatial scale of the rainfall field and the average rain gauge density can be extremely significant.

This impacts the probability of observing the actual peak rainfall and can lead to an overestimation of the return period associated with the most intense events, which are of interest for the design of hydraulic structures and risk planning.

The dramatic underestimation of the rainfall depth at very high return periods due to the application of traditional statistical methods has been already highlighted as a criticality in the literature, focusing on daily rainfall. This work presents a first attempt to set up a framework to quantify the underestimation of the precipitation peak (or the overestimation of the return period) at sub daily scale as a function of the ratio between the raingauge density and the transversal dimension of the precipitation events.

How to cite: Boni, G., De Angeli, S., Lagasio, M., and Parodi, A.: How the spatial structure of extreme rainfall observed by meteo-radars can impact the estimation of the return period of extra-ordinary events?, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 12–15 Oct 2021, Plinius17-95, https://doi.org/10.5194/egusphere-plinius17-95, 2021.

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Italy is one of the countries most exposed to hydrogeological risk in Europe. From the hydrological point of view, alluvial phenomena and rainfall-induced landslides have a common origin, since both of them are caused by intense surface runoff causing slope instability or water overflow in the drainage network. In particular, the territory of central Italy has a complex orography, where heterogeneous basins with different areas co-exist. Vast basins such as that of the Tiber, are found in geographical areas contiguous to minor hydrographic basins, which are mainly located along the eastern slope of the Apennines. Due to this complexity of the landscape, the territorial response to precipitation can be different and alluvial phenomena can be the result of different processes, with the precipitation as a common denominator. Floods or flash floods, but also rainfall-triggered landslides represent the main effects at the ground, due to intense or persistent rains. In general, river floods are considered more predictable than flash floods, since the latter are linked to very localized rain events, concentrated over a short period of time. The predictability of landslides is associated with attentive monitoring, based on the definition of rainfall thresholds.In this work, the hydrological model developed by Cetemps (CHyM) is applied for the simulation and detection of areas subjected to hydrological stress of a large geographical domain, which includes all of Central Italy, during diverse severe weather event impacting Central Italy in the recent years. We propose the validation of three different stress indices on a geographical area of ​​about 65 500 km2, including basins of very different sizes and characterized by heterogeneous substrates. The main purpose is to present a unique tool for the forecast on a regional scale of hydrogeological stresses induced by precipitation. The identification of stress conditions is given through the use of indices, able to detect areas affected by floods, flash floods and landslides, also providing a key to discriminate and classify these three different phenomena.

How to cite: Lombardi, A., Colaiuda, V., Gallicchio, D., Boscaino, G., Raparelli, E., Tuccella, P., Lidori, R., Rossi, F. L., Liberatore, S., and Tomassetti, B.: User-oriented indices for rainfall-related hydrogeological hazards prediction at regional scale: validation in Central Italy, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 12–15 Oct 2021, Plinius17-59, https://doi.org/10.5194/egusphere-plinius17-59, 2021.

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The Italian peninsula has one of the highest hydrogeological risk levels in Europe, characterised by a geomorphologically varied and geologically complex territory. In particular, mountainous areas are characterized by fragile environments that are frequently affected by floods and instability.

The weather events that have struck our country in recent decades have often triggered/reactivated natural instability processes that have been particularly damaging in terms of structures and infrastructure. In mountainous and hilly areas, both muddy-debris flows and surface landslides are particularly widespread. The former is triggered within secondary basins, often fed by surface landslides, and are particularly evident on alluvial conoids, affecting population centers. There are many variables, both meteorological and territorial, that make forecasting these phenomena very difficult.

In view of the intensification of these severe weather events, it is important to set up an advanced hazard forecasting system in mountain locations that allows geological analyses to be integrated with atmospheric and hydrological modelling. In this context, the identification of areas susceptible to landslides cannot be performed using a conventional approach, since hydrological-hydraulic methods have a poor or poor calibration.

In response to the need of fast communication to make the Early Warning System more effective, allowing an immediate assessment of the risk and its spatial and temporal location, we propose the use of specially designed indices that, although deduced from the predicted physical fields, allow warning messages to be provided both on the basis of observed and predicted rainfall, and on the basis of the flow forecasts of the monitored rivers and their main tributaries.

We therefore propose a new approach, based on a forecasting chain that brings together geomorphological information, reliable high-resolution weather forecasts and hydrological models.

In this work, a pre-operational chain was set up, coupling off-line the high-resolution Weather Research and Forecasting (WRF) meteorological model and the Cetemps Hydrological Model (CHyM). Different stress indices were calculated useful to identify the debris flows of the Croso river and possible criticalities on the other river basins.

How to cite: Tomassetti, B., Ferrarese, S., Golzio, A., Colaiuda, V., Luciani, M., Tuccella, P., and Lombardi, A.: Early Warning System for hydrogeological risk forecasting in mountain environments: The Rio Croso case study., 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 12–15 Oct 2021, Plinius17-62, https://doi.org/10.5194/egusphere-plinius17-62, 2021.

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Water-age accounting, and its stable isotopic signature due to fractionation, is becoming a powerful tool in gaining further insights in several science questions related to watershed hydrologic response in extreme weather events and its sensitivity to land and climate changes. Experience is quite limited on fully distributed watershed models capable of explicitly tracking water age and stable isotopes variations along the modelled fluxes. Most of these models rely on a full-mixing simplifying hypothesis inside each model conceptual reservoir, e.g. a soil layer in a computational pixel or a river reach. This hypothesis is known to seriously affect the capability of matching model results with isotope data, especially at time scales much shorter than the seasonal one, hence preventing efficient data assimilation to improve model calibration ad state estimation. We propose here a water age-and-isotope tracking version of the fully distributed watershed model MOBIDIC, which in its standard operational version includes surface energy-mass balance, snowpack dynamics, hydraulic river and reservoir routing, surface-groundwater interactions. An augmented EnKF isotope and river discharge data assimilation framework is also presented based on such a model, aimed at both estimating key model parameters and improving the estimation of river water partitioning among different sources during floods. While input hydrometeorological data used in the experiments refer to real high-flow events on a mid-size mountain basin, synthetic data are generated (with an ideally ‘unknown’ set of model parameters) for river flows and isotopes in a first assimilation efficiency assessment presented here.

How to cite: Castelli, F. and Arrighi, C.: Water-Age Accounting, Fully Distributed Watershed Modeling for Flood Forecasting, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 12–15 Oct 2021, Plinius17-75, https://doi.org/10.5194/egusphere-plinius17-75, 2021.

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Maghreb countries are strongly impacted by floods, causing twice as many deaths as in southern European countries in recent decades. However, due to the lack of data accessibility, there are no studies to analyze whether the frequency or intensity of floods are changing at the regional scale. In this work, a recent database of daily river discharge data from 58 basins located in Algeria, Morocco and Tunisia with on average 32 years of complete records over the time period 1970-2017 is considered to analyze the evolution of floods. A peaks-over-threshold sampling of flood events is considered, to detect trends on the annual frequency and the magnitude of floods. The results illustrate the complexity of conducting trend detection in a context of high inter-annual variability, with spurious trends detected in several cases due to isolated extreme events. Overall, few statistically significant trends are detected on the intensity of floods but an increase in flood frequency is detected in one-third of the basins. The results are interpreted in relation to land-use change, river regulation by dams and reservoirs, and climatic change. Recommendations concerning the use of frequency analysis approaches on floods in this region are given.

How to cite: Tramblay, Y., El Khalki, E. M., Benaabidate, L., Boulmaiz, T., Boutaghane, H., Dakhlaoui, H., Hanich, L., Ludwig, W., Meddi, M., Sadaoui, M., El Mehdi Saidi, M., and Mahé, G.: Changes in flood hazards in North Africa and implications for flood frequency analysis, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 12–15 Oct 2021, Plinius17-87, https://doi.org/10.5194/egusphere-plinius17-87, 2021.

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Barcelona constitutes a good example of a Mediterranean coastal megacity that can be severely affected by climate change impacts. The urban heat island effect, which is particularly important in Barcelona could magnify direct impacts on health produced by the frequency and intensity increase in heat waves and tropical nights. If we consider the Metropolitan Area of Barcelona (AMB) where 52.8% of its surface area is urban, is possible to see maximum temperatures higher than 35 °C in the city center, with minimum nighttime temperatures above 23°C, while coastal peri-urban areas register 4°C less than in the city. Besides this, in a warmer climate, the risk of floods might also increase. Floods are relatively frequent in the AMB with more than 3 pluvial flood episodes per year and over 7 Million €₂₀₁₅ paid for flood damages between 1996 and 2014 by the national insurance company “Consorcio de Compensación de Seguros”.

Nevertheless, the impacts of these events across the city are heterogeneous and highly dependent on its urban planning, socioeconomic distribution, topography, and the characteristics of the meteorological systems affecting it. As a result, Barcelona resilience has a strong dependence on local factors that must be accounted for in the design of any management plan or adaptation strategy that must be adopted by the municipality, its citizens or socioeconomic actors. In this context of hydrometeorological risks that are going to worsen over time, and with the goal of improving resilience in a sustainable way, the Barcelona Living Lab on Extreme Events (Barcelona LLEE) was born under the auspices of the I-Change (Individual Change of HAbits Needed for Green European transition) project and in collaboration with the C3-RiskMed project.

This communication begins with the knowledge about intense rains, floods, and extreme temperatures in AMB, continues with the strategy that will govern the Living Lab, and ends with the methodological proposal that will govern the experiment. The first part is based in the application of the Local Climate Zones to do a classification of the different land covers and land uses of AMB and obtaining the spatial distribution of temperature at high resolution in present and future scenarios as well as its impact in the risk mortality (Gilabert et al., 2021).  On the other hand, flood events have a heterogeneous effect across the city due to differences in the urban planning, its topography, the distinct socioeconomic distribution, and the intrinsic characteristics of these precipitation systems that have been analysed through the meteorological radar and considering information provided by the company responsible of the drainage system (Esbrí et al., 2021). The second part shows the seven points of the strategy that governs the Barcelona LLEE and pretends to engage citizens and stakeholders in the project for Green European transition.  Finally, the methodology includes the use of the App FLOODUP in the framework of citizen science.

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement 101037193, and the “Ministerio de Ciencia e Información” (project PID2020-113638RB-C22).

How to cite: Llasat, M. C., Llasat-Botija, M., Marcos, R., Esbrí, L., Racionero, S., Rigo, T., Gilabert, J., and Corbera, J.: From scientific knowledge to individual change of habits: the Barcelona Living Lab on extreme events , 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 12–15 Oct 2021, Plinius17-13, https://doi.org/10.5194/egusphere-plinius17-13, 2021.

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Flood-producing rainfall events often lead to material damage to buildings, vehicles, and infrastructure with a significant cumulative economic impact. Especially in urban areas, vulnerability to floods may vary at the local level, and so are the rainfall amounts likely to trigger flood damages. Insurance claims for flood damages can accurately indicate when and where these occurred. In the frame of the YANTAS project (project code:T2EDK-01108), a detailed insurance claims dataset of one of Greece's most important private insurance companies was used, combined with the dense surface weather station data provided by the METEO unit of the National Observatory of Athens. The aim was to model flood damage occurrence and identify the triggering rainfall thresholds at the local level across the Athens Metropolitan Area. Namely, we used eight-year rainfall observations from 66 meteorological stations and insurance claims on the postal code segmentation for the analysis. Logistic regression was applied to statistically model flood damage occurrence. We further applied the ROC curves to assess the performance of the binary response models and define optimal 24-h rainfall thresholds. The method is performed at the municipal level, as municipalities are the first administration level where decision-making to address the local risks for the citizens is needed. The rainfall thresholds were further classified to estimate and map the local risk of flood damages. The applicability of the detected thresholds in early-warning systems is also discussed.

How to cite: Papagiannaki, K., Kotroni, V., Lagouvardos, K., Bezes, A., Vafeiadis, V., Messini, I., Kroustallis, E., and Totos, I.: Examining flood damage occurrence at the local level as a function of rainfall, based on insurance claims across an urban Mediterranean region, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 12–15 Oct 2021, Plinius17-8, https://doi.org/10.5194/egusphere-plinius17-8, 2021.

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Jerusalem City is unique in its diversity of populations with a
total of 936,000 inhabitants (end of 2018) with 62% Jewish and 38% Arabs,
and is located exactly at the border of Mediterranean climate with a significant
variability between the coastal area, including Jerusalem City (annual rainfall
~600 mm) and the most arid zone of the Dead Sea, 20-30 km east of the city
(annual rainfall ~50 mm). The spatial-temporal variation of rainfall
intensity is the main and not well-known driver that generates the majority of flash floods in the nearby Judean Desert. Hence, its monitoring is crucial in this area as in other remote arid areas worldwide.

Recently, extensive research was performed related to global warming potential risks and their effects on rainfall and temperature over the East Mediterranean. Several major risks were pointed out including extreme temperatures, heat waves, colder nights and heavy rainfall. Important to notice is our first super-high-resolution global climate model projections that the ancient “Fertile Crescent” in the Middle East (considered as the cradle of civilization), will nearly disappear during this century by the year 2100 (Kitoh et al. 2008).

Jerusalem temperatures both maximum and minimum show that significant increases occurred during 1950-2020 (based on homogenized dataset, Yosef et al., 2019). Furthermore, enhanced increases are shown to have occurred from the 1980s of the temperature trends which are even more than double of the global average ones. A fact that led to definition of the Mediterranean as a “Hot Spot” of global warming. Comparison of Jerusalem temperatures increasing trends to the coastal upstream Bet Dagan station, at ~40 km to the west does show similar patterns of statistically most significant increases in the region as well as large inter-annual variabilities.

A general reduction in the annual amount was observed in the last four decades over Jerusalem. This tendency is expected to continue and become more pronounced under the "business as usual" scenario of RCP8.5. Some potential socioeconomic impacts will be presented.

How to cite: Alpert, P., rubin, Y., and yosef, Y.: Challenges related to Climate Change and Identification of Risks and Impacts  in Jerusalem, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 12–15 Oct 2021, Plinius17-97, https://doi.org/10.5194/egusphere-plinius17-97, 2021.

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Models for the assessment of direct flood impacts are widely applied, while models for indirect impacts and cascading effects are still in a theoretic and demonstration phase. The division of damage into direct and indirect is commonplace, but interpretations and delineations of what is considered a direct and indirect impact differ. Direct damages are usually associated with the physical contact with flood water, thus almost instantaneous, and generally estimated by stage-damage functions. All the consequences beyond the physical damage are considered indirect impacts and include effects occurring outside the inundated area in space and time. This work presents two modelling frameworks capable of describing the space and time dimensions of indirect flood impacts. The first model simulates the water supply system (WSS) of a metropolitan area and the effect of the service disruption for users in case of floods. The second model simulates the recovery after a flood and it is specifically tailored for describing resilience of art cities, where cultural heritage makes the difference in socio-economic impacts. Both models are applied to the metropolitan area of Firenze (Italy) as a proof of concept. The results show how significant space and time extents of indirect impacts are, when compared to direct ones and this drive the need for a better understanding of system perspectives in flood risk management.

How to cite: Arrighi, C. and Castelli, F.: Exploring space and time dimensions of indirect impacts of floods, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 12–15 Oct 2021, Plinius17-77, https://doi.org/10.5194/egusphere-plinius17-77, 2021.