Session PL1 

Mediterranean coastal regions are regularly affected by sudden heavy precipitation events leading to very dangerous flash floods. The structures responsible for extreme precipitation episodes are typically intense and small-sized quasi-stationary V-shaped mesoscale convective systems, repeatedly affecting the same area for several hours. Severe rainfall prediction, being the result of many mutually interacting multiscale processes, not yet completely understood and modeled, is still a major challenge for numerical weather prediction (NWP) systems. Furthermore, the intrinsic uncertainty related to deep moist convection and the large sensitivity of precipitation to uncertainties in the initial and boundary condition decrease the skill of numerical models, even at high horizontal resolution and short forecast times. In recent times, artificial intelligence (AI) emerged as a powerful tool for handling vast amounts of data and extracting patterns and relationships that might be challenging to identify through traditional fully-deterministic algorithms.

In the framework of the AIxtreme (Physics-based AI for predicting extreme weather and space weather events) project, a suite of AI-based techniques is being developed to calibrate numerical models based on the physics of the atmosphere, with the aim of anticipating the occurrence of extreme weather events and supporting decisions of civil protection agencies.

Thanks to the combined exploitation of deterministic weather prediction models and efficient data-driven AI-based algorithms, operational weather forecasts with improved accuracy in relation to key meteorological observables such as wind, temperature and precipitation, are expected to become available. A first significant result of the project is the development of a deep learning framework, named FlashNet, able to forecast able to forecast lightning flashes up to 48 h ahead in terms of probability of occurrence. FlashNet is capable to find an optimal mapping of meteorological features predicted two days ahead by the state-of-the-art numerical weather prediction model by the European Centre for Medium-range Weather Forecasts (ECMWF) into lightning flash occurrence. The prediction skill of the resulting AI-enhanced algorithm turns out to be significantly higher than that of the fully deterministic algorithm employed in the ECMWF model. A remarkable Recall peak of about 95% within the 0-24 h forecast interval is obtained. This performance surpasses the 85% achieved by the ECMWF model at the same Precision of the AI algorithm.

How to cite: Cassola, F., Carnevale, D., Sacchetti, D., Tizzi, M., Cavaiola, M., and Mazzino, A.: Combined exploitation of deterministic and AI-based tools for severe weather prediction, 18th Plinius Conference on Mediterranean Risks, Chania, Greece, 30 Sep–3 Oct 2024, Plinius18-45, https://doi.org/10.5194/egusphere-plinius18-45, 2024.

Lightning can influence many human activities, being a threat also for human lives. The Mediterranean area is prone to thunderstorms and lightning. In this context, lightning forecast plays a fundamental role. We studied the impact of lightning data assimilation (LDA) on lightning and precipitation forecast over Italy and over part of the Central Mediterranean Basin. First, we highlight some characteristics of strokes over Italy and the Central Mediterranean [1], considering data over 13 years recorded by LINET (LIghtning NETwork). The analyses of the records show that lightning activity occurs mainly in summer and fall; moreover, a substantial change of convection characteristics between the two season is apparent. In summer, convection occurs over the land, in fall it is mainly over the sea.

Then, we consider a two-seasons data assimilation experiment [2] running the Weather Research and Forecasting (WRF) model coupled with the Dynamic Lightning Scheme (DLS) at 3km horizontal resolution for summer 2020 and fall 2021. Each simulation produced the forecast for the following 6h. Therefore, the representation of a whole day needs four different simulations. Verification is done over two sub-periods, 0-3h and 3-6h after assimilation. Results for the 0-3h phase show a positive impact of LDA on strokes forecast, both improving correct forecasts and reducing false alarms. Depending on the case, LDA can trigger convection missed by control forecast and can correct strokes’ patterns, leading to predictions more in agreement with observations. An improvement compared to the previous day forecast, without LDA, is also obtained. Therefore, the forecast over the 0-3h phase with LDA is applicable to issue warnings and alerts as the storm is approaching. LDA forces convection where lightning is observed. Consequently, lightning forecast improvement given by LDA, is more evident over the land in summer and over the sea in fall. The 3-6h phase show a negligible impact of LDA on strokes forecast.

References

[1] Marco Petracca, Stefano Federico, Nicoletta Roberto, Silvia Puca, Leo Pio D'Adderio, Rosa Claudia Torcasio, Stefano Dietrich. A 13-year long strokes statistical analysis over the Central Mediterranean area, Atmospheric Research, Volume 304, 2024, 107368, ISSN 0169-8095, https://doi.org/10.1016/j.atmosres.2024.107368.

[2] Stefano Federico, Rosa Claudia Torcasio, Jana Popova, Zbyněk Sokol, Lukáš Pop, Martina Lagasio, Barry H. Lynn, Silvia Puca, Stefano Dietrich, Improving the lightning forecast with the WRF model and lightning data assimilation: Results of a two-seasons numerical experiment over Italy, Atmospheric Research, Volume 304, 2024, 107382, ISSN 0169-8095, https://doi.org/10.1016/j.atmosres.2024.107382.

How to cite: Federico, S., Torcasio, R. C., Petracca, M., Roberto, N., Puca, S., and Dietrich, S.: Lightning over Italy: analyses of data and impact of their assimilation on lightning and precipitation forecast, 18th Plinius Conference on Mediterranean Risks, Chania, Greece, 30 Sep–3 Oct 2024, Plinius18-54, https://doi.org/10.5194/egusphere-plinius18-54, 2024.

Accurate weather forecasts are important to our daily lives. Wind, cloud and precipitation belong to the fundamental variables in NWP models. The WIVERN (Wind Velocity Radar Nephoscope) mission (Illingworth et al., 2018), for observing global winds, clouds and precipitation, has the opportunity to be the first space-based mission to provide in-cloud winds. It is currently in the phase A of the European Space Agency (ESA) Earth explorer 11 program and, if demonstrated successful, WIVERN data could be beneficial to enhance NWP performance, to improve our knowledge of weather phenomena, and to validate climate statistics.

In this work, we present an assimilation experiment of the WIVERN Doppler (HLoS; Horizontal winds along the Line of Sight) data for the outstanding case of the Medicane Ianos, occurred in mid September 2020.

To this end, we use the following approach: we run the Medicane Ianos with WRF at 4km horizontal resolution using the ECMWF-EPS (European Centre for Medium range Weather Forecast – Ensemble Prediction System) analysis/forecast cycle issued at 12 UTC on 16 September 2020 as initial and boundary conditions. Fifty-one occurrences of the Medicane Ianos (members) are forecast, taking into account for the atmospheric predictability of that day. For all members the trajectory of the Medicane is determined by the minimum surface pressure.

The trajectories are then compared with the reference trajectory determined by the method of Flaounas et al. (2023) that makes use of ERA5 reanalysis and the best member among the 51 WRF simulations is determined. The best member is that minimizing the spatial error compared to the reference trajectory. WIVERN pseudo-observations are then generated for the best member using the Wivern simulator (Battaglia et al., 2022). Pseudo-observations are then assimilated into the WRF model every 3h using the 3DVar scheme of Federico (2013). Results show a positive impact of the data assimilation on the simulation of the Ianos trajectory. The distance between the simulations assimilating HLoS and the best trajectory are more than halved compared to the control forecasts.

Sensitivity tests to the observation error and to the WIVERN revisiting time show that the latter has a much larger impact on the quality of the forecast.

References

Battaglia, A., et al., 2022, https://doi.org/10.5194/amt-15-3011-2022.

Federico, S., 2013, https://doi.org/10.5194/amt-6-3563-2013.

Illingworth, A. J., et al., 2018, DOI: 10.1175/BAMS-D-16-0047.1, 1669-1687.

Flaounas, E., et al., 2023, https://doi.org/10.5194/wcd-4-639-2023

How to cite: Federico, S., Torcasio, R. C., Montopoli, M., Panegrossi, G., Cambiotti, C., and Battaglia, A.: Assimilation of WIVERN Doppler data in WRF model for the case study of Medicane Ianos, 18th Plinius Conference on Mediterranean Risks, Chania, Greece, 30 Sep–3 Oct 2024, Plinius18-20, https://doi.org/10.5194/egusphere-plinius18-20, 2024.

Between Sept. 4, 2023, and Sept. 12, 2023, a cyclogenesis develops close to the Greek coast in the Ionian Sea. The evolution of this cyclone is divided into two phases: a strongly baroclinic one with intense orographic precipitation in Greece, and a final barotropic phase with the formation of an intense tropical-like cyclone (TLC) impacting Libya, causing more than 10,000 deaths due to the intense precipitation causing the sudden break of a dam. In this work, we investigate this TLC (named “Daniel”) initially using the standalone WRF model with different sea surface temperature sensitivity tests until we arrive at the use of the coupled atmosphere-ocean and atmosphere-ocean-wave models. The purpose of this work is to investigate the role of each environmental component in the development of the barotropic phase and the record-breaking precipitation. We also aim to study the energy fluxes and mixing factors between the atmosphere and the ocean. Preliminary results show that SST plays a crucial role in the intensification of the cyclone and precipitation, not only along the cyclone track but especially in the neighboring areas, where high values of heat transport are found.

How to cite: Ricchi, A., Ferretti, R., Pantillon, F., Dafis, S., and Saúl Carrió Carrió, D.: On the role of air-sea-wave interaction in developing destructive Tropical-Like Cyclones DANIEL, 18th Plinius Conference on Mediterranean Risks, Chania, Greece, 30 Sep–3 Oct 2024, Plinius18-63, https://doi.org/10.5194/egusphere-plinius18-63, 2024.

In the early morning of 1 August 2021, a supercell developed over the Veneto plain and moved eastward towards Friuli-Venezia Giulia, locally producing hailstones with diameters up to 9 cm.

In the present work, this event is studied by means of simulations with the Weather Research and Forecasting (WRF) model at 1 km resolution, coupled with the HAILCAST hail growth parameterization, which provides estimates of the maximum hail size at the ground. Several simulations are performed using different initial and boundary conditions (GFS and IFS forecasts), different initialization times and physics options, to study the predictability of the event.

The analysis of the model results highlights a significant sensitivity to the forcing meteorological model and the initialization time. In particular, WRF is not able to properly simulate the development of strong convection over the Veneto and Friuli-Venezia Giulia plain in the early morning of 1 August using GFS forcing, while better results are obtained with IFS initial and boundary conditions, especially when simulations are initialized more than 24 hours before the event. Moreover, results are significantly affected by the microphysics scheme and the land surface model, while the planetary boundary layer parameterization seems to have a minor influence. However, the development of the supercell is properly simulated, with hailstone diameters comparable to observations, only when data from radiosoundings of Udine Rivolto are nudged into the model, highlighting the importance, and at the same time the complexity, of correctly reproducing local thermodynamic conditions for the simulation of extreme convection events.

How to cite: Perbellini, A., Sioni, F., Manzato, A., and Giovannini, L.: Numerical simulations of a supercell in northeastern Italy with WRF-HAILCAST, 18th Plinius Conference on Mediterranean Risks, Chania, Greece, 30 Sep–3 Oct 2024, Plinius18-72, https://doi.org/10.5194/egusphere-plinius18-72, 2024.

Mediterranean tropical-like cyclones, also known as medicanes, are small cyclones observed in the Mediterranean region with an average frequency of 1-2 cases per year, mainly in autumn and winter. The tropical-like phase of these cyclones is characterized by the presence of a symmetric thermal structure and a deep warm core, which are features typical of tropical cyclones. Their mechanisms of formation and tropical transition have been investigated by many authors, but an official rigorous definition of medicane is still lacking, due to the significant case-by-case differences.

In this work, 17 Mediterranean cyclones, including three potential medicanes in 2023, have been first analyzed using the ERA5 reanalysis dataset to evaluate their similarities and dissimilarities, considering different features in the lower and upper troposphere. Results show that the development of a warm core is negatively correlated with potential vorticity (PV) in the upper troposphere, while PV increases in the low troposphere due to latent heat release. It has also been verified that during the tropical-like phase the wind shear presents lower values, the jet stream is weaker and farther from the cyclone center, and the cyclone is vertically aligned, even if some exceptions exist. Then, the presence of a dry intrusion has been investigated using back-trajectories, showing that all cyclones present descending dry air associated with a PV streamer, meaning that the upper-level dynamics are fundamental in the early stages. However, the threshold of 400 hPa of descent in 48 hours used in literature to define the dry intrusion is not appropriate for cyclogenesis in the Mediterranean, and, in some cases, a weaker PV streamer associated with a less pronounced descent is sufficient for cyclogenesis. In this regard, Ianos, one of the strongest medicanes ever recorded, presents two weak descending flows associated with PV streamers, one in the early stage and one before the strong deep warm core phase. This cyclone has also been analyzed through a simulation with the WRF model with a grid spacing of 3 km, with the main aim of evaluating the different terms of the pressure tendency equation (PTE), to quantify the role of upper-level dynamics and diabatic heating on the surface pressure tendency. The same procedure has been applied to analyze the recent cyclone Daniel that affected Libya in September 2023, and a comparison with Ianos has been performed.

How to cite: Nigro, D., Bordoni, S., Giovannini, L., and Miglietta, M. M.: The peculiarities of Ianos among Mediterranean tropical-like cyclones, 18th Plinius Conference on Mediterranean Risks, Chania, Greece, 30 Sep–3 Oct 2024, Plinius18-115, https://doi.org/10.5194/egusphere-plinius18-115, 2024.

The North-western Mediterranean coast, including the Catalan littoral zone, faces a high probability of extreme weather events. Climate change exacerbates these challenges by increasing the frequency and intensity of phenomena like droughts, heatwaves, and flooding. The Metropolitan Area of Barcelona, with its dense urban environment and complex topography, struggles with significant hydrological challenges, especially during intense, localized downpours. Efficient drainage is difficult due to the region's coastal location and urban landscape.

To enhance urban resilience, this study emphasizes the importance of using non-structural and structural techniques that mimic natural hydrologic responses, thereby reducing adverse runoff impacts. Understanding the dynamics of convective precipitation at high resolution is crucial for sustainable water management and flood resilience in Barcelona. Improved knowledge of storm structures and rainfall patterns can help predict and mitigate extreme weather effects in the metropolitan area.

This work introduces a radar-based nowcasting approach that utilizes a two-dimensional radar product with three-dimensional atmospheric information to improve early warnings for the urban region with high spatial resolution. Unlike previous methods that relied single levels of radar reflectivity such as CAPPI and TOP (Esbri et al., 2021), this new approach focuses on the most convective parts of storms by incorporating Vertical Integrated Liquid (VIL) density-based nowcasting. The VIL density product, derived from radar composites, provides vertical storm structure information in a two-dimensional format, enabling faster data processing without losing volumetric capabilities.

The obtained storm centroid distributions using the two different methodologies are discussed. The new resulting warning areas are compared with incidents from Barcelona's rainfall drainage network, managed by Barcelona Cicle de l’Aigua S.A., and the economic impacts collected by the Consorcio de Compensación de Seguros for municipalities in the Metropolitan Area of Barcelona, thereby redefining rainfall hotspots in the region.

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement 101037193.

References:

Esbrí L., Rigo T., Llasat M.C., Aznar B. Identifying Storm Hotspots and the Most Unsettled Areas in Barcelona by Analysing Significant Rainfall Episodes from 2013 to 2018. Water. 2021; 13(13):1730. https://doi.org/10.3390/w13131730

How to cite: Esbri, L., Rigo, T., Aznar, B., and Llasat, M. C.: Radar based nowcasting to enhance urban resilience to flash floods in the Metropolitan Area of Barcelona , 18th Plinius Conference on Mediterranean Risks, Chania, Greece, 30 Sep–3 Oct 2024, Plinius18-109, https://doi.org/10.5194/egusphere-plinius18-109, 2024.

SEE-MHEWS-A project aims to provide operational forecasters from 17 National Meteorological and Hydrological Services of the South-East Europe with effective and tested tools for forecasting hazardous weather events and their possible impacts in order to improve the accuracy of warnings and their relevance to stakeholders and users. On a single virtual platform, the system collects NWP information for the provision of accurate forecasts and warnings to support hazard-related decision-making by national authorities. In addition to the operational IFS model of the European Centre for Medium-Range Weather Forecasts (ECMWF), four limited area model (LAM) configurations for South-East Europe (SEE) are developed and run in a quasi-operational environment including: ALADIN-ALARO, COSMO, ICON, and WRF NMM-B. Our interest is a structured, region-wide forecast verification as a necessary component of the process to establish a multi-hazard early warning system.

We study strengths and weaknesses of different modelling systems in different weather situations to provide an initial estimate of model success in a real-time operational situation for precipitation, including extreme events, over a pilot area of wider eastern Adriatic coast spanning over five countries. First, our approach uses moment-based and categorical statistical verification, including a decomposition of scores into biases and dispersion (phase) errors. Best results averaged over all stations are not achieved for a single model but vary across several modelling configurations depending on the score analyzed. It is clearly noticeable that models are of lower accuracy near the mountainous coast compared to continental inland due to the generally more intense precipitation, influence of the complex terrain and influence of sea and surface inhomogeneities. Likewise, categorical verification suggests low-medium intensity precipitation forecast accuracy is the lowest where Dinaric Alps are most complex, but results do improve in higher precipitation categories. Although results are far from perfect for most extreme events, all models show skillful predictions and none of the models shows considerably more strengths than others with extremal dependence index (EDI) ranging from 0.45 up to 0.85 depending on the model.

To alleviate effects of small errors in time and space on verification measures, in absence of spatially homogenous precipitation data, we apply a neighborhood verification approach, which offers an alternative that rewards closeness by relaxing the requirement for exact matches between forecasts and observations in the spatial domain. The single-observation neighborhood approach (SO-NF) results show an improvement in ETS values with an increase of the spatial scale for the categories of events. At the highest precipitation category (above 30 mm/24h) and common spatial scale of ~45 km, ECMWF and COSMO models seem to perform somewhat more consistently than other models. Nevertheless, the improvement of the results with the forecast neighborhood size noticed for most models and countries shows the benefits of the SO-NF approach in terms of recognizing additional forecasted values present in the proximity of the exact location, even though they were slightly displaced.

How to cite: Horvath, K., Odak Plenković, I., and Keresturi, E.: Evaluation of precipitation forecasts of several NWP modelling systems within South-East European Multi-Hazard Early Warning Advisory System - SEE-MHEWS-A project, 18th Plinius Conference on Mediterranean Risks, Chania, Greece, 30 Sep–3 Oct 2024, Plinius18-132, https://doi.org/10.5194/egusphere-plinius18-132, 2024.

An extremely intense and organized convective storm, classified as a “derecho”, developed over the western Mediterranean Sea on August 18, 2022. The system affected Corsica, northern Italy, and Austria, with wind gusts up to 62 m/s and giant hailstones (diameter of around 11 cm), being responsible for 12 fatalities and 106 injured people.

The derecho developed over an extreme and persisting marine heatwave over the western Mediterranean. Therefore, the hypothesis of a relationship between the atmospheric event and the marine heatwave rapidly arose, suggesting a possible link with anthropogenic climate change.

By performing model simulations with both the Model for Prediction Across Scales (MPAS) and the nonhydrostatic operational AROME model and using the pseudo-global warming approach, we find a relationship between the marine heatwave, the actual anthropogenic climate change conditions, and the development of this extremely rare and severe convective event. These results suggest the increase of probability of development of similar events with respect to the past associated to climate change, and illustrate how climate change effects can cascade through a chain of extreme weather and climate events.

How to cite: González-Alemán, J. J., Insua-Costa, D., Bazile, E., González-Herrero, S., Miglietta, M. M., Groenemeijer, P., and Donat, M. G.: Attribution of the destructive Mediterranean derecho in 2022 to anthropogenic warming, 18th Plinius Conference on Mediterranean Risks, Chania, Greece, 30 Sep–3 Oct 2024, Plinius18-3, https://doi.org/10.5194/egusphere-plinius18-3, 2024.

In the Mediterranean region, there is no consensus in trends of observations of extreme rainfall events, nor agreement between models in multi-models’ projections. Yet, extreme rainfalls in the Mediterranean region poses significant risks to human life, infrastructure, and ecosystems. In this context, our work aims to better understand the physical processes leading to changes in extreme rainfall in the region. The region of study is the Western Part of the Mediterranean. 

We investigate the topic conducting a Pseudo-Global-Warming experiment. We simulated two 10 years periods with WRF at a convection-permitting resolution, which helps to  capture extreme rainfall events more realistically. One simulation is for the period 2011-2020, fed by ERA5 reanalysis (past-present), and another simulation for the same period, but with a climate change signal - extracted from 27 GCM (Global Climate Models) – added to the ERA5 data from 2011-2020. The GCM signal is calculated for a high-emission scenario (SSP585) and the period 2070-2099 with respect to 1985-2014.

We show how the characteristics of events producing extreme rainfalls could change in a warmer climate, focusing on their size, intensity, localization, and durations. Furthermore, we provide insights of the physical processes driving these changes by exploring the relationship between extreme rainfall and indicators of atmospheric conditions favoring their occurrence. For example, we show the connection between high Convective Available Potential Energy (CAPE) and extreme rainfall, both in the present and in a warmer future.  We also examine how often extreme rainfall events coincide with convective storms or cyclones, and explore how the relationship between storm occurrence and extreme rainfall may change in a warmer future climate.

Our findings offer valuable understanding of the complex dynamics of extreme rainfall events in the Western Mediterranean region, providing crucial insights into the potential impacts of climate change on this vulnerable area.

How to cite: Bahuet-Bourret, Y. and Argüeso, D.: Understanding the influence of a warmer climate on the processes leading to Extreme Rainfalls in the Western Mediterranean. A Pseudo-Global-Warming experiment., 18th Plinius Conference on Mediterranean Risks, Chania, Greece, 30 Sep–3 Oct 2024, Plinius18-37, https://doi.org/10.5194/egusphere-plinius18-37, 2024.

The Mediterranean Sea is experiencing accelerated warming, outpacing the global ocean average according to recent studies. This regional basin is particularly susceptible to the effects of climate change due to its unique topography and thermohaline circulation patterns. Observational data and model reanalysis have documented significant changes in the characteristics of Mediterranean water masses.

One of the best indicators of this alarming trend is the Ocean Heat Content (OHC). The challenge of this research manifests in the implementation of a cloud-based workflow to estimate the OHC, assessing its evolution in user-defined sub-regions or depth layers within the Mediterranean basin. This application developed within the EU Blue Cloud 26 project framework, has the ambition to access data machine-to-machine data from multiple blue data infrastructures (SeaDataNet, Copernicus Marine Service, EuroArgo, World Ocean Database) available to the scientific community.

The workflow will use the DIVAnd tool to map historical in situ temperature data on a regular grid and the results will be compared to ocean reanalysis products from INGV and the Copernicus Marine Service.

The analysis will focus on identifying OHC trends, with a specific emphasis on understanding the implications of these changes for the region's climate system.

We expect the results to highlight the spatial variability of warming trends within different sub-regions and depth layers, underscoring the complex interplay between hydrodynamics and climate change in shaping the Mediterranean's thermal structure.

Moreover, by leveraging this workflow, we ensure that ocean key variables are consistently updated and validated according to the most recent community practices. The effort conducted will allow us to have a key indicator, such as OHC, rapidly available and constantly updated according to the most recent data, thus supporting an informed and efficient decision.

Finally, this study will contribute to the broader understanding of regional climate dynamics and provide valuable insights into the diagnosis and projection of extreme weather events in the Mediterranean Sea within the context of a changing climate environment.

How to cite: Baglione, E., Finlayson, M., and Simoncelli, S.: Diagnosis and Projection of Mediterranean Sea Warming Trends within the Framework of a Generalized Workflow, 18th Plinius Conference on Mediterranean Risks, Chania, Greece, 30 Sep–3 Oct 2024, Plinius18-64, https://doi.org/10.5194/egusphere-plinius18-64, 2024.

This study explores future projections of climate extreme indices in Central Europe and examines the impact of performance-based subsetting of Global Climate Models (GCMs). To achieve this, we evaluated CMIP6 GCMs based on their accuracy in replicating the observed mean, spatial correlation, and variability of selected climate extreme indices. We analyzed simulations from all available CMIP6 models under four socio-economic scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5), using two baseline periods (1961-1990 and 1981-2010) and two future periods (2021-2050 and 2070-2099). The study considered three air temperature indices: (i) the number of days with daily maximum temperature over 34 °C (Su34), (ii) the number of days with daily maximum temperature over 25 °C (Su25), and (iii) the number of tropical nights with daily minimum temperature over 20 °C (TN). Additionally, we analyzed four rainfall indices: (i) number of days with very heavy precipitation over 20 mm (R20mm), (ii) number of days with heavy precipitation over 10 mm (R10mm), (iii) consecutive dry days (CDD), and (iv) consecutive wet days (CWD) for precipitation thresholds of 1 mm and 2 mm. Our ranking method assigned scores to the models from 1 to 39 for each climate extreme index based on three evaluation metrics: Pearson’s correlation coefficient, the ratio of the mean, and the ratio of the standard deviation. The total rank for each GCM was determined by summing these scores across all indices and metrics.

The median of the multi-model ensemble (MME) indicates an important increase in the number of days with very heavy and heavy precipitation, especially towards the end of the century, while the number of consecutive wet days shows minimal change. Consecutive dry days are projected to increase significantly by the late 21st century. There is also a marked rise in the number of summer days and tropical nights, with more pronounced changes in the southern regions of the study area.

We selected the top ten models ensemble (BME) based on their performance ranking. For historical periods, the BME showed improved accuracy for the mean of all indices except Su34. For future projections, the BME indicates greater positive changes in very heavy precipitation and consecutive wet days compared to the MME. Conversely, the BME shows smaller changes for Su34 and Su25 indices, particularly for the far future period. The interquartile range (IQR) of R10mm and R20mm is higher for the BME than for the MME. The BME's IQR for CDD is also higher, except under SSP585, where it narrows in both future periods. The IQR for CWD remains similar between the BME and MME, with a higher IQR only under SSP126. For Su25 and Su34, the BME exhibits a higher IQR under all scenarios except SSP585 in the near future. Regarding tropical nights, the BME reduces the IQR across all scenarios while maintaining the MME medians.

How to cite: Dhib, S., Halenka, T., Holtanova, E., Verma, S., and Belda, M.: Ranking and projection of CMIP6 based on Climatic Extremes performance over Central Europe, 18th Plinius Conference on Mediterranean Risks, Chania, Greece, 30 Sep–3 Oct 2024, Plinius18-107, https://doi.org/10.5194/egusphere-plinius18-107, 2024.

The potential increase of heat stress is a major challenge of the 21st century, and the Mediterranean region is especially exposed to this natural hazard due to the anthropogenic global warming. This study evaluates the multi-model and multi-scenario ensemble from global climate model simulations - available from the CMIP6, i.e. Coupled Model Intercomparison Project Phase 6 of the World Climate Research Programme - including four different SSP-RCP scenario pairs (i.e. from immediate rapid mitigation and effective adaptation, SSP1-RCP2.6, to no mitigation with highly challenging adaptation, SSP5-RCP8.5). For this purpose, the Interactive Atlas of the IPCC AR6 Working Group 1 is used, and the geographical differences of climate projections are compared within the Mediterranean region of Europe. The study provides key information so the regional and national adaptation strategies for different socio-economic sectors can be built and/or updated accordingly.

This study focuses on temperatures extremes, i.e. the monthly frequency of heat days with daily maximum temperature above 35 °C. The target periods cover two decades on medium-term (2041-2060) and long-term (2081-2100), and the reference period is defined as the last two decades of the historical simulation period (1995-2014). Several zonal and meridional segments were defined over Europe, along which the projected changes are analysed with a special focus on sea cover, continental, and topography effects. Furthermore, the consequences of different scenarios are also compared. The results clearly show that greater radiative forcing change implies more severe health effects via the more frequent heat stress events. However, substantial differences can also be identified from south to north as well, as from west to east. The study highlights the differences within the Mediterranean region.

Acknowledgements: Research leading to this study has been supported by the European Climate Fund (G-2309-66801), the Hungarian National Research, Development and Innovation Fund (under grants PD-138023 and K-129162), and the National Multidisciplinary Laboratory for Climate Change (RRF-2.3.1-21-2022-00014).

How to cite: Pongrácz, R., Divinszki, F., and Kis, A.: Analysis of projected changes of heat days frequency within the Mediterranean region using CMIP6 simulations, 18th Plinius Conference on Mediterranean Risks, Chania, Greece, 30 Sep–3 Oct 2024, Plinius18-129, https://doi.org/10.5194/egusphere-plinius18-129, 2024.