It is currently assumed that anthropogenic climate change has differentially altered the probabilities of extreme events occurring in the development of certain meteorological phenomena, such as temperatures and precipitation, in many regions of the planet. But, there is little or no consensus on its impact on African Dust Outbreaks (ADO). The objective of this study was to estimate the contribution of global warming (thermodynamic factors) and of changes in certain atmospheric circulation types (CT, dynamic factors) to the detected increase in the development of ADO over areas of Spain (Salvador et al., 2022).

To this end, values of daily probability of ADO occurrence (PROB-ADO) over eight regions of Spain in 1940-2024, were calculated with numerical prediction models (Salvador et al., 2024). ERA5 daily fields of temperature and geopotential height at different levels were used to calculate the thermodynamic parameters that feed the models and to generate daily synoptic CT maps at 850 hPa at 12 UTC. PROB-ADO extremes were thus defined as days on which PROB-ADO exceeded the 90^th percentile of the time series of daily values for the period 1940-2024.

Then, a circulation classification methodology was applied to group all days of this period into one of the 11 characteristic CTs identified by Salvador et al. (2022). Six out of the 11 patterns, were identified as ADO-CTs.

To calculate temporal trends in the time series of annual frequencies of the 11 CTs and of values of PROB-ADO and PROB-ADO extremes over 1940-2024, the Theil-Sen methodology was used. Finally, to determine the dynamic, thermodynamic and interactive contributions of each individual CT to the general trend in the occurrence of PROB-ADO extremes, the quantitative partitioning methodology proposed by Horton et al. (2015) was applied.

Statistically significant increasing trends in PROB-ADO extremes were obtained in all 8 zones for the period 1940–2024. Trend estimators ranged from 0.016 days/year in the NW zone to 0.628 days/year in the SE. There was a clear decreasing gradient along the SE-NW axis. Thermodynamic contributions were predominant, ranging from 41% in the NW to 94% in the SE sector. The dynamic contribution was smaller and varied between 9% in the SE zone and 47% in the NW. Mixed contributions were very small, ranging from -4% to 12%, and are mostly negative, indicating that this type of interaction didn’t contribute to an increase in the trend for PROB-ADO extremes. The largest overall contribution (increases of between 0.01% and 0.18% of the days in the year) came from ADO-CT1 (between 31% and 67% of the trend) and, to a lesser extent, ADO-CT6 (between 10% and 31%). Our results indicate that although a substantial portion of the observed change in PROB-ADO extremes has resulted from thermodynamic changes, it has also been altered by recent changes in the frequency of ADO-CTs.

Acknowledgements

This research received support from MITECO and from project POSAHPI-2 (ref. PID2022-143146OB-I00).

References

Horton, D.E. et al., 2015, https://doi.org/10.1038/nature14550.

Salvador, P. et al., 2022, https://doi.org/10.1038/s41612-022-00256-4.

Salvador, P. et al., 2024, https://doi.org/10.1016/j.scitotenv.2024.171307.

How to cite: Salvador, P., Scofield, D., Pey, J., Pérez, N., Alastuey, A., Querol, X., and Pujadas, M.: Recent trends in probability of African dust outbreaks occurrence over Spain: Quantitative partitioning of dynamic and thermodynamic effects., 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-13, https://doi.org/10.5194/egusphere-plinius19-13, 2026.

Large-scale atmospheric circulation exerts a primary control on environmental variability over the western Mediterranean, where African dust outbreaks strongly affect aerosol loading, radiative balance, air quality, and ecosystem dynamics. Although recent decades have shown substantial interannual variability in African dust transport towards Iberia and the Mediterranean Basin, uncertainties remain regarding the long-term evolution of dust-favourable synoptic conditions under climate change. Here we investigate the past, present, and future evolution of atmospheric circulation regimes associated with African dust outbreaks using a multi-source framework that combines reanalysis datasets, CMIP6 climate simulations, observational dust records, and sedimentary archives.

Daily atmospheric circulation states were characterised using 850 hPa geopotential height fields over North Africa and the western Mediterranean. We applied a fixed-centroid weather-regime classification consistently across modern reanalyses, long-term historical reconstructions, and climate model simulations. The classification identifies 11 recurrent synoptic circulation regimes, of which 6 are significantly associated with enhanced African dust transport towards Iberia and the western Mediterranean (Salvador et al, 2022). Dust relevance was validated using independent observational datasets, including satellite-constrained aerosol products and observational catalogues of African dust outbreaks over the Iberian Peninsula.

To extend the analysis beyond the satellite and modern observational period, we incorporated long-term reanalysis products such as the NOAA 20th Century Reanalysis, allowing reconstruction of circulation variability back to the 19th century. This enabled us to assess whether the recent increase in dust-favourable circulation patterns is unprecedented within the context of the last ~200 years, and to evaluate multidecadal variability linked to large-scale modes of atmospheric circulation. We further compared these reconstructed circulation trends with historical simulations from CMIP6 models.

Multi-model ensembles are then used to assess future changes under SSP1-2.6 to SSP5-8.5 scenarios. Preliminary results show that dust-related circulation regimes represent ~58% of days in the historical baseline period (1980–2014). Both ERA5 and the CMIP6 historical ensemble show positive trends in dust-favourable circulation occurrence (~+0.69% and +0.67% per decade, respectively). Future projections indicate a robust intensification of these conditions throughout the 21st century, particularly under high-emission scenarios. Under SSP5-8.5, trends reach nearly +1.94% per decade, suggesting a substantial increase in the persistence and recurrence of atmospheric configurations conducive to African dust transport. Results also indicate a seasonal expansion of dust-conducive circulation into spring months.

Additionally, we intend to explore the feasibility of using sedimentary evidence of African dust deposition in lacustrine archives from the Iberian Peninsula and the Pyrenees. These high-resolution sediment records may provide an independent paleoclimatic benchmark to evaluate the realism of reconstructed atmospheric circulation and inferred dust variability over longer timescales. Ongoing analyses include hyperspectral imaging, geochemical tracers, and mineralogical indicators associated with North African dust inputs. By integrating atmospheric dynamics, climate model simulations, historical reanalyses, and sedimentary evidence, this work aims to improve the diagnosis and long-term understanding of extreme aerosol transport events in a changing climate and to provide a more robust framework for evaluating future dust-related hazards in the Mediterranean region.

How to cite: Scofield-Teruel, D., Salvador, P., Valero-Garcés, B. L., and Pey, J.: Past and Future Changes in African Dust-Favourable Atmospheric Circulation over Iberia, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-22, https://doi.org/10.5194/egusphere-plinius19-22, 2026.

Heatwaves (HWs) are among the most damaging climate extremes affecting the Mediterranean basin, where they could drive excess mortality, agricultural losses, water stress and wildfire risk. The Mediterranean region is warming fast, and the frequency, duration and intensity of HWs are projected to keep rising. Anticipating these events requires understanding their drivers. The complex interaction between large-scale atmospheric circulation, remote teleconnections and local land-surface conditions is difficult to capture with conventional statistical or dynamical approaches, and these drivers may vary markedly from one Mediterranean sub-region to another.

This work proposes the application of a general driver identification framework, Spatio-Temporal Cluster-Optimized Feature Selection (STCO-FS), to identify the key short-term and seasonal drivers of HWs across the Mediterranean basin. The method combines clustering algorithms for reducing the spatial dimensionality with an ensemble evolutionary optimization algorithm to perform driver selection jointly in the spatial and temporal domains. In a first phase, gridded predictor fields from the ERA5 reanalysis, such as mean sea level pressure, geopotential height at 500 hPa, sea surface temperature, soil moisture, total precipitation and 2 m temperature, are reduced in dimensionality by grouping grid points with similar temporal behaviour into clusters. Climate variability indices (e.g. NAO, ENSO, IOD) and local variables are added directly. In a second phase, a wrapper feature selection approach based on a multi-method evolutionary algorithm (PCRO-SL) selects the most skilful drivers and identifies, for each one, the optimal time lag and time window, distinguishing short-term precursors (days) from sub-seasonal and seasonal influences (up to several months) of HW occurrence.

The framework will be evaluated on representative areas of the Mediterranean. We expect that this approach will allow us to unravel the relative contribution of the different variables, and to characterise how these contributions differ across sub-regions of the basin. By revealing the spatio-temporal structure of HW drivers, this framework aims to improve the physical understanding and sub-seasonal predictability of Mediterranean HWs, supporting more effective early warning and climate adaptation strategies.

How to cite: Pérez-Aracil, J., Peláez-Rodríguez, C., McAdam, R., Squintu, A., Cornejo-Bueno, L.-M., Scoccimarro, E., Luterbacher, J., Giuliani, M., Xoplaki, E., Castelleti, A., and Salcedo-Sanz, S.: Identifying the spatio-temporal drivers of Mediterranean heatwaves: a machine learning feature selection framework, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-89, https://doi.org/10.5194/egusphere-plinius19-89, 2026.

In recent decades, Europe has experienced a marked increase in the frequency and intensity of heatwaves, a trend projected to continue under future climate change. The Mediterranean basin is particularly vulnerable to these extremes, making it crucial to better understand the processes controlling their development and persistence. Among these, land-atmosphere interactions influence the exchange of water and energy between the land surface and the atmosphere and can either amplify or mitigate extreme heat conditions. At the same time, future land-use and land-cover changes (LULC) are expected to modify these exchanges, although their impact on heatwave-related feedback remains poorly quantified.
In this study, we investigate the influence of evolving LULC on land-atmosphere coupling and heatwave characteristics under future climate conditions across Europe, with particular emphasis on Mediterranean regions. Simulations were performed with the Weather Research and Forecasting model (WRF v4.5.1.4) under the SSP3-7.0 scenario within the EURO-CORDEX and LUCAS Phase 2 frameworks. A standard experiment with fixed 2015 land cover is compared with a transient LULC simulation in which land cover evolves annually following the Land Use Harmonization (LUH2) protocol.
Extreme temperature days are identified using percentile-based thresholds of daily maximum temperature (TX90p), while heatwaves are defined as periods of at least five consecutive exceedances. To assess land-atmosphere feedback during these events, coupling metrics are computed from normalized temperature, latent heat flux, and soil moisture variables, allowing consistent comparisons across regions and simulations. The analysis focuses on the relationships between TX90p and latent heat flux (TX90p x LH) and between TX90p and soil moisture (TX90p x SMOIS), allowing the identification of coupled and decoupled surface-atmosphere regimes.
By linking future changes in land cover to variations in coupling strength during extreme heat events, this work aims to improve our understanding on the physical mechanisms controlling future heatwave intensity and persistence, and to assess the extent to which land-use may influence future heat-related climate risks.

Acknowledgements
The authors wish to acknowledge the financial support from the Portuguese Fundação para a Ciência e Tecnologia (FCT, I.P./MCTES) through national funds (PIDDAC): LA/P/0068/2020 - https://doi.org/10.54499/LA/P/0068/2020, UID/50019/2025, https://doi.org/10.54499/UID/PRR/50019/2025, UID/PRR2/50019/2025.
L.C.S. and R.M.C. also acknowledge individual funding from FCT, I.P./MCTES grants https://doi.org/10.54499/UI/BD/154675/2023, and https://doi.org/10.54499/2021.01280.CEECIND/CP1650/CT0006.

How to cite: Santos, L., Cardoso, R. M., Navarro Montesinos, J., García Bustamante, E., González Rouco, J. F., DaCamara, C., and Soares, P. M. M.: How do land-atmosphere interactions shape future heatwaves in Mediterranean climate hotspots?, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-115, https://doi.org/10.5194/egusphere-plinius19-115, 2026.

Evidence of global warming is clearly reflected in extreme daily maximum temperature events, particularly when record-breaking temperatures occur. In the Iberian Peninsula, previous studies showed that the frequency of such records exhibits a non-stationary behaviour, with an upward trend and strong spatial variability. In this work, we build a statistical model to explore and interpret the spatial heterogeneity and spatio-temporal structure of this phenomenon.

Daily maximum temperature (T_x) series from 36 meteorological stations across Spain covering the period 1960-2023 were obtained from the European Climate Assessment & Dataset. Predictor variables were obtained from ERA5 reanalysis data, consisting of geopotentials at 300, 500, and 700 hPa at 12:00 UTC, covering a 1º x 1º grid spanning [45º N, 10º W, 35º S, 5º E]. The analysis was restricted to the summer season (JJA).

A previously developed modelling framework was applied to obtain station-specific logistic regression models, as well as global models. The response variable was defined as a binary indicator of extreme heat event (EHE) occurrence. For each station s, the event threshold was defined as the 95th percentile of T_x in the reference period 1981-2010, computed over summer days only. Formally, the threshold is given by u_s = Q_0.95 (T_x,t,l t ∈ [1981, 2010], l ∈ [1, 92]) where T_x,t,l denotes the daily maximum temperature at station s on day l of year t. An EHE is then defined through the indicator I_x,t,l = 1 if T_x,t,l > u_s , and 0 otherwise, with value 1 indicating the occurrence of an EHE.

The modelling strategy was carried out in three steps: (1) stepwise logistic regression was performed independently at each station to identify relevant predictors; (2) the most frequently selected and influential variables across stations were used to construct a global model; and (3) three extended models were developed by incorporating interactions with geodesic, climatic, and spatial covariates, followed again by stepwise selection. The first 51 years of the period were used for building the models and the final 13 years were reserved for validation. Due to class imbalance, model performance was evaluated using the AUC measure.

The best results were obtained from the global model including climatic interactions, which reached an AUC of 0.89 with k = 34 parameters and was therefore selected as the winning model. The individual geopotential terms of this model were analysed to better understand the climatic characteristics associated with EHEs. It was also used to simulate EHEs over the validation period. The simulated EHE sequences were compared with the observations in order to evaluate the model’s ability to reproduce consecutive-day heatwave dynamics. In addition, the model’s assigned probabilities of EHE occurrence were assessed during selected heatwave episodes in the validation period.

How to cite: Barrio-Torres, E., Gracia-Tabuenca, Z., Castillo-Mateo, J., Asín, J., Cebrián, A. C., and Abaurrea, J.: Statistical Modelling of Extreme Heat Events Using Geopotential Height Covariates, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-37, https://doi.org/10.5194/egusphere-plinius19-37, 2026.

Mediterranean heatwaves are among the most impactful extreme weather and climate phenomena, with significant impacts on human health, ecosystems, energy demand, and water resources. The Mediterranean basin is widely recognized as a climate change hotspot, where the frequency and intensity of summer temperature extremes are projected to increase. However, important uncertainties remain regarding the representation and predictability of heatwave-related atmospheric conditions at seasonal timescales.

This study investigates major Mediterranean heatwave events during the 1991–2010 period using high-resolution, dynamically downscaled hindcast simulations produced with the Weather Research and Forecasting (WRF) model, driven by ERA5 and CFSR reanalysis data. Heatwave conditions are identified using ETCCDI indices, e.g. TX95p and TX99p, enabling a consistent characterization of moderate and extreme temperature events in terms of intensity, duration, and spatial extent across the Mediterranean region.

The analysis focuses on a set of prominent historical heatwave episodes within the study period and examines their associated large-scale atmospheric conditions and regional circulation features. Particular attention is given to the ability of the simulations to reproduce the timing, spatial patterns, and persistence of these events, as well as the broader atmospheric environments in which they develop.

To evaluate model performance and predictability, all WRF-based simulations are analyzed at a common 3-month lead time, allowing for a uniform examination of their ability to reproduce heatwave-relevant circulation regimes and extreme temperature characteristics. This includes an evaluation of event representation, spatial patterns, persistence, and associated large-scale circulation features. The comparison provides insight into the capabilities and limitations of dynamical downscaling for representing Mediterranean heat extremes.

Overall, the study aims to improve the understanding of Mediterranean heatwave behavior and to evaluate the capability of regional dynamical downscaling systems and seasonal forecast models to represent and anticipate extreme summer temperature conditions.

Acknowledgements: This research was supported by the PREVENT project that has received funding from the EU Horizon Europe framework programme (grant no. 101081276) / Part of the results presented in this work have been produced using the Aristotle University of Thessaloniki (AUTh) High Performance Computing Infrastructure and Resources.

How to cite: Velikou, K., Manios, E. M., Papadopoulos Zachos, A., Tolika, K., and Anagnostopoulou, C.: Seasonal Predictability and Dynamical Representation of Mediterranean Heatwaves Using WRF Simulations, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-27, https://doi.org/10.5194/egusphere-plinius19-27, 2026.

Extreme precipitation is one of the most dangerous meteorological phenomena, causing significant harm to people, structures, and crops, as well as resulting in economic losses. Due to their resolution and configuration, Convection-Permitting Models (CPMs) offer the potential to reproduce convective extreme precipitation. However, CPM simulations require long runtimes and generate large amounts of data, consuming significant computer storage. Therefore, it is necessary to establish a link between extreme events in CPMs and their counterparts in global climate models (GCMs) and regional climate models (RCMs). Identifying this link would allow selective use of CPMs only for days when significant precipitation is expected, reducing the need to run climate simulations over extended periods and focusing on specific days.

Three methods were tested for detecting potential extreme precipitation events in CPMs using GCM data: a fixed precipitation threshold, linear regression, and logistic regression. Convective precipitation and calculated instability indices (Lifted Index, K Index, CAPE, wind shear, moist convergence and wind convergence) were used in the selected GCM, EC-Earth. The methods were trained using the outputs of the CPM HCLIM38-AROME over the Scandinavian domain in the historical period (1986–2005). This domain was chosen for training because of the availability of longer time series, and it was further divided into three smaller subdomains for improved method evaluation. Additionally, RCM simulations (HCLIM38-ALADIN) were used to enhance the detection of extreme events. The RCM bridges the gap in grid spacing between the GCM and the CPM. For validation, standard statistical methods were used, such as hit rate, Matthews correlation coefficient, and ROC score.

Initial results using a convective precipitation threshold in the GCM show relatively successful forecasting of extreme precipitation in the CPM, with a hit rate of 0.42. Calculating instability indices and introducing linear and logistic regression further improve the results, increasing the hit rate to 0.51. When moving to smaller subdomains within the same period, the performance of all methods decreases somewhat, but linear and logistic regression remain effective in predicting days with extreme precipitation (hit rate varies from 0.35 to 0.43).

The next step was to introduce the intermediate RCM as an additional filter. With this modification, the extreme precipitation prediction results reach a hit rate of 0.65.

Finally, the methods are validated over the same domain for the same models in the future period (2081–2100), as well as over the pan-Alpine domain, which includes parts of the Mediterranean and Croatia, in the period 1996–2005. The results indicate that by using linear regression and the RCM as a filter, extreme precipitation events can largely be detected already in the GCM, allowing selective inclusion of the CPM, which leads to savings in computational resources and time.

How to cite: Omazić, B., Oštrić, S., Karaula, L., and Belušić, D.: Detection of potential extreme precipitation events in convection-permitting climate simulations using statistical methods in global climate models, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-30, https://doi.org/10.5194/egusphere-plinius19-30, 2026.

Adverse convective weather (including large hail, heavy rainfall, downbursts and tornadoes) has been identified as one of the main research focuses due to its high impact on densely populated regions. Some recent examples in the western Mediterranean are: giant hail in Catalonia (2022 and 2023) and northern Italy (2024), floods in Valencia and the Ebro Delta (2020, 2021, 2023 and 2024), or the August 2022 derecho (Balearic Islands, Corsica and northern Italy). Furthermore, this impact seems to be increasing in some areas, such as the Mediterranean basin itself, for several reasons.

This analysis considers a continuous period of 12 years (2014-2025) of 6-minute radar data to provide insight into convective behaviour and trends in Catalonia (NE Iberian Peninsula). We investigated those pixels defined as convective: reflectivity at low levels between 25 and 75 dBZ and maximum reflectivity at any level between 45 and 75 dBZ. For each pixel, the surface and maximum reflectivity, the 45 dBZ echotop, the coordinates and the time (date plus time) were estimated. We evaluated, spatially, monthly and annually, the occurrence of these pixels, among other properties (recurrence, area, events, etc.). This presentation introduces the first results of our research: an increase in convective activity during the warmest season (from June to August), particularly in areas with high topography; only in some areas does convective activity decrease slightly; and an overall positive trend of all the variables studied throughout the period. These results are consistent with other studies indicating increased convection associated with changes in the freezing level or the amount of precipitable water at lower levels.

How to cite: Rigo, T., Marcos-Matamoros, R., and Llasat, M. C.: Deep analysis of convective trends in Catalonia, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-52, https://doi.org/10.5194/egusphere-plinius19-52, 2026.

Drought is a recurring phenomenon in the Mediterranean climate that characterizes the Iberian Peninsula, but its manifestations vary in duration, extent, and severity. Studying it using current instrumental meteorological records poses no difficulties, and techniques exist for its calculation and graphical and cartographic representation. However, to understand the patterns of this phenomenon in its most severe and least frequent manifestations, one must rely on historical documentary sources that allow drought impacts to be identified and analysed at daily temporal resolution over the last five centuries.

In this study, we used data from the AMARNA platform, which contains 12,012 cases or units of information distributed in 1,672 drought episodes from 1450 to 1950 for the whole of Spain. This information on droughts has been obtained from historical documentary sources containing records of liturgical rogation ceremonies for rain (“pro pluvia”). These ceremonies were commissioned by municipal authorities to address this adversity, which affected the development of agricultural crops.

Each case corresponds to a specific rain-praying ceremony that was held and recorded in the official records. All records available in AMARNA have been subjected to a series of filters to exclude sporadic or scattered information from the analysis, and to focus the analysis on the episodes of greatest relevance and information density. Having access to AMARNA data allows us to characterise the behaviour of major drought episodes during the Little Ice Age and to place them in the context of the instrumental period.

Using data on recorded cases from AMARNA, a methodology has been developed to classify drought episodes according to their duration, spatial extent, intensity and documentary evidence density. The proposed classification provides a framework for identifying and comparing the most significant drought episodes currently known in Spain between 1450 and 1950. It also offers new opportunities to investigate long-term drought variability, spatial patterns, and the occurrence of extreme events during the Little Ice Age and the transition to the modern climatic period.

Acknowledgements

The authors acknowledge the grants from FLOODMED (PID2024-157662OB-C22), funded by the Spanish Ministry of Science, Innovation and Universities (MICIU/AEI/10.13039/501100011033) and by ERDF/EU.

How to cite: Barriendos, J., Gil-Guirado, S., Pérez-Morales, A., Wimberly, F., Ummenhofer, C., Cuadrat, J. M., Jover, G., and Mariano, B.: Temporal evolution of drought in Spain over the last 500 years using historical documentary sources and instrumental records, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-68, https://doi.org/10.5194/egusphere-plinius19-68, 2026.

Extreme precipitation events are among the major hazards in the Mediterranean region, owing to their multiple impacts on natural and human systems. Their characterisation and physical understanding have been the focus of decades of research, particularly in the context of changes driven by global warming. These events are frequently associated with cut-off lows, which may also involve the advection of cold air at the surface. However, events producing concurrent extreme rainfall and snowfall within hydrological basins have received comparatively less attention.

In late December 1944, one such event caused severe impacts in the Segura River Basin, in southeastern Spain, generating both flooding and snowfall of extraordinary magnitude. Some observatories recorded precipitation totals reaching 220 mm over consecutive rainy days, while several villages became isolated by snow depths of up to one metre. The event resulted in fatalities and substantial socioeconomic impacts. This study aims to improve our understanding of cold–wet compound extreme events in the Mediterranean region by characterising this historical case study and assessing changes from 1941 to 2021 through the identification of circulation-analogue events. To this end, we combine newspaper sources, precipitation and temperature observations, and ERA5 reanalysis data. Beyond the analysed case study, the main results indicate changes in the surface impacts associated with these events over recent decades. Overall, no increase in event frequency is detected, nor is there a robust signal of changes in atmospheric dynamics. However, analogue events in the recent period produce more precipitation, with an average increase of 9.4 mm per event compared to earlier-period analogues, and are warmer on average, mainly due to an increase in minimum temperature of 1.1 °C per event. These results point to changes in the characteristics of cold–wet compound extreme events under recent climate conditions.

Overall, this study highlights how integrating historical event reconstruction with circulation-analogue methods improves the understanding of compound extremes in the Mediterranean region. The results also illustrate how global warming is altering the surface impacts of these events, with relevant implications for flood risk and water resource management.

How to cite: Halifa-Marín, A., Calvo-Sancho, C., Gil-Guallar, M., Royo-Aranda, A., Vela-Tambo, J., Adell-Michavila, M., Torres-Vázquez, M. A., Franquesa, M., Lemus-Canovas, M., Domínguez-Castro, F., Latorre, B., El Kenawy, A. M., Beguería, S., and Vicente-Serrano, S. M.: Insights into the December 1944 Extreme Cold–Wet Event in Southeastern Spain: Evidence of Change in Its Present-Day Analogues, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-101, https://doi.org/10.5194/egusphere-plinius19-101, 2026.

The North-Western Mediterranean region, which is a semi-enclosed sea surrounded by mountains, is prone to severe events. The region is notably known as a key spot for strong wind, like mistral and tramontane, channelled and accelerated in the surrounding valleys, that induces sometimes damaging sea states. Heavy precipitation events also often occur when a moist and rapid marine low-level flow converges and/or encounters mountainous area, triggering and feeding stationary deep convective systems that lead to very localized, large amounts of rainfall in only some hours (typically more than 100 mm in less than 24 hours), generating flash-floods. Furthermore, the region is more and more frequently affected by (marine) heatwaves that intensify with climate change and have major impacts on public health, agriculture/fishery and biodiversity. All these extreme events rely on air-sea interactions during their onset and lifecycle, with complex responses and feedbacks in terms of ocean as atmospheric circulation and processes.

To better represent the mesoscale air-sea environment and the exchanges in numerical modelling and weather prediction systems, fine horizontal resolution and coupling are crucial. The AROBASE system assembles kilometer-scale limited-area models of the atmosphere, the ocean, and waves. Since summer 2024, a first AROBASE forecast demonstrator is applied daily over the Metropolitan France region. It couples the AROME numerical weather prediction model at 1.3 km resolution and the NEMO ocean model with a 1/36° resolution. A second version was deployed in autumn 2025 and adds a new coupling to take into account the impacts of waves on the air-sea exchanges. This study will present some comparisons of the atmosphere-ocean(-waves) AROBASE forecast with the (uncoupled) AROME operational forecast during recent severe meteorological situations that affected the North-Western Mediterranean region.

How to cite: Lebeaupin Brossier, C., Beuvier, J., Bouin, M.-N., Dalphinet, A., and Nicolay, F.: High-resolution atmosphere-ocean coupling impact on North-Western Mediterranean severe event forecasts with the AROBASE prediction system, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-61, https://doi.org/10.5194/egusphere-plinius19-61, 2026.

For over two decades, the State Meteorological Agency of Spain (AEMET) has developed and operated Limited-Area Ensemble Prediction Systems (LAM-EPS) to quantify forecast uncertainty and provide reliable predictability guidance for short-range high-impact weather events. Currently, the operational AEMET-γSREPS functions as a convection-permitting, multi-model, and multi-boundary condition ensemble. Deploying operational domains over the Iberian Peninsula, the Canary Islands, and the Antarctic Peninsula, this system supplies forecasters with a comprehensive suite of probabilistic products to assess diverse atmospheric scenarios and support adverse weather warning mechanisms. This presentation reviews the institutional trajectory of LAM-EPS at AEMET and outlines future strategic directions. Key upcoming milestones include the transition toward a single-model HarmonEPS system incorporating Stochastically Perturbed Parameterizations (SPP), developed within the collaborative frameworks of ACCORD-EPS and UWC-South.

How to cite: Gómez-Navarro, J. J. and Callado-Pallarès, A.: LAM-EPS Systems at AEMET: Evolution, Current Capabilities, and Future Perspectives, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-81, https://doi.org/10.5194/egusphere-plinius19-81, 2026.

Reliable Numerical Weather Prediction (NWP) are of utmost importance to our daily life. In addition, they are of fundamental to help mitigation of severe and catastrophic weather events.

Atmospheric water vapor is a fundamental element of weather forecasting, nevertheless its accurate observation is difficult, mainly because of its high spatiotemporal variability. 

A reliable way to estimate water vapor is through Global Navigation Satellite Systems (GNSS) satellites, whose signals are received from ground-based stations and permit to calculate Zenith Total Delay (ZTD). ZTD can be easily related to Precipitable Water Vapor (PWV). 

The GNSS observation at the zenith uses delays from different directions to improve the estimate of the delay in the vertical direction, thus strengthening the solution. This process, however, reduces the number of observations available for each GNSS receiver. Anyway, the high quality of GNSS observations in the zenit direction has become a reference for other instruments and has been widely assimilated in NWP models worldwide.

Estimating the delay in different directions poses challenges for the convergence of the solution and for errors in the retrieved slant total delay (STD). Similarly, while the assimilation of the zenith delay for GNSS receivers is well-established, the assimilation of the delay in the inclined directions remains largely unexplored.

In this work, GNSS information along slant paths is assimilated into the Weather Research and Forecasting (WRF) model. Two approaches are shown: the first considers the assimilation of the delay along slant paths, the second the assimilation of precipitable water vapor along slant paths.

In the first approach, the assimilation of STD is done through the use of tropospheric gradients in the East and North directions. Gradients assimilation has been recently added in a version of the WRFA Data Assimilation (WRFDA) and presented in the paper of Thundathil et al. (2024). The same method was applied in Torcasio et al. (2026). 

An application of GNSS gradients assimilation over Italy is presented. The impact on the precipitation prediction of GNSS gradients assimilation both alone or in combination with GNSS-ZTD data assimilation is shown for a case study, comparing the results with a model configuration not assimilating GNSS data. Results show an improvement when GNSS data assimilation is applied: event intensity and location are better represented and false alarms are reduced. The configuration assimilating both GNSS-ZTD and gradients has the best performance. 

A second experiment considers PWV data assimilation along slant paths (PWVS). In this case, the STD signal is converted in precipitable water vapor and assimilated in WRF, increasing the number of observations in comparison to the assimilation of precipitable water vapor in the vertical direction. We consider an experiment of one month showing the problems involved in the assimilation of PWVS, its results, and its comparison with corresponding forecast without the assimilation of GNSS observations and with the assimilation of GNSS delay in the zenith direction.

References

Torcasio R.C. et al. (2026) https://doi.org/10.1007/s12210-025-01399-1

Thundathil R. et al. (2024) https://doi.org/10.5194/gmd-17-3599-2024 

How to cite: Torcasio, R. C. and Federico, S.: Assimilation of GNSS delays along slant paths into the WRF model: two experiments over Italy, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-96, https://doi.org/10.5194/egusphere-plinius19-96, 2026.

Tornadoes and waterspouts in the western Mediterranean and Iberian region are low-frequency but potentially damaging hazards, whose spatial occurrence remains difficult to characterize using fixed geographical or climatological regions. This limitation is especially relevant for risk-sensitive applications, where local exceedance probabilities and return-period estimates require physically meaningful regional occurrence rates.

This work presents an objective framework for the environmental regionalization and probabilistic hazard assessment of tornado and waterspout occurrence over peninsular Spain and the Balearic Islands. A unified and quality-controlled event catalogue was built by merging national (SINOBAS/AEMET) and European (ESWD/ESSL) severe weather records, yielding 1185 tornado and waterspout events for the period 1992–2025 after duplicate removal. For each event, pre-event atmospheric environments were characterized using ERA5-derived thermodynamic, kinematic, and composite instability parameters extracted around the event location and time.

To move beyond fixed a priori regions, event environments were spatially aggregated over a hexagonal grid of approximately 50 km and summarized through robust environmental signatures. Dimensionality reduction via principal component analysis, followed by Ward hierarchical clustering with spatial connectivity, identified three objective environmental regions. These clusters provide a physically based spatial partition of tornado-favourable environments and are evaluated against a priori subregional divisions using supervised machine learning classifiers.

Building on this regionalization, the study develops an occurrence, point-scale exceedance, and 50-km neighbourhood return-period framework for tornadoes. Regional tornado rates are estimated by intensity class and combined with Monte Carlo path-geometry simulations and internal wind-speed exceedance fractions. These were used to derive exceedance curves EP(v,T) and threshold-based hazard maps consistent with the observed spatial heterogeneity of tornadic environments.

Results show that the data-driven regions capture coherent environmental regimes — shear-dominated in the west and southwest, thermodynamically charged in the central-southeast, and weakly forced in the north and east — that are not fully reproduced by fixed geographical subdivisions. A key outcome is a decoupling between occurrence and severity: the regimes that produce most tornadoes are not those that dominate the high-end wind hazard, since the least active, thermodynamically charged regime concentrates the most intense events and controls exceedance at the highest thresholds. The proposed framework provides a reproducible basis for tornado hazard mapping in Spain and the Balearic Islands, with potential applications to civil protection, territorial planning, and the assessment of risk-sensitive infrastructures.

How to cite: Agurto Barragán, G., Aroba Páez, J., Gutiérrez Álvarez, I., and Gutiérrez de San Miguel Herrera, E.: A data-driven regionalization and point-scale exceedance framework for tornado and waterspout hazard assessment in peninsular Spain and the Balearic Islands, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-33, https://doi.org/10.5194/egusphere-plinius19-33, 2026.

Although the definition of medicanes has been recently provided (Miglietta et al., 2025), the characteristics of the most intense among these cyclones have yet to be determined. This latter subcategory of medicanes includes cyclones that, during their mature phase, are driven almost exclusively by air-sea interaction and are responsible for the greatest damage.

In this context, we analyze 17 medicanes using ERA5 reanalysis data to study the role of upper-tropospheric processes in cyclone development. Using back-trajectory analysis, we investigated the presence of dry intrusions in the early and mature phases of cyclones. We found that the standard definition of a dry intrusion, characterized by a descent of 400 hPa in 48 hours, is rarely met. In contrast, weaker and shallower descents associated with PV streamers are more common. Although dry intrusions can accelerate warm core formation by promoting convection, the final intensity of the warm core depends critically on diabatic processes near the cyclone's center, as exemplified by Ianos.

In fact, in Ianos only marginal descending flows occur before the main tropical phase, yet this cyclone develops the most intense warm core among the analyzed cyclones. This prompted us to examine Ianos in detail using a WRF model simulation with a 3 km grid spacing. This simulation highlights the dominant contribution of diabatic heating to the cyclone's intensification already in the early stages and suggests a secondary role for the baroclinic forcing, indicating a different pathway in the cyclone's evolution. However, in the mature phase, a weak upper-level PV streamer contributes to the rapid deepening of the cyclone.

How to cite: Miglietta, M. M., Nigro, D., Giovannini, L., Bordoni, S., and Dafis, S.:  Toward the identification of different subcategories of medicanes, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-91, https://doi.org/10.5194/egusphere-plinius19-91, 2026.

This study investigates Storm Samuel (Medicane JOLINA), a cyclone that developed over the central Mediterranean during March 2026 and subsequently affected North Africa and Libya. The system originated as a baroclinic cyclone in the lee of Tunisia, evolving through a warm-seclusion phase before acquiring tropical-like characteristics during the final stages of its life cycle. The event therefore provides an ideal framework for exploring the mechanisms governing the transition between extratropical and tropical-like structures in the Mediterranean environment. A hierarchy of numerical experiments is performed using the Weather Research and Forecasting (WRF) model at convection-permitting resolution. Simulations include configurations with and without spectral nudging, experiments using observed high-resolution SST fields and SST fields from which mesoscale anomalies have been removed, a suite of uniform SST perturbation experiments, and a pseudo-global-warming (PGW) simulation based on the ensemble-mean climate change signal derived from multiple future projections. An ocean mixed-layer parameterization is employed to account for air–sea coupling processes. The results indicate that cyclone genesis and propagation are primarily controlled by large-scale atmospheric forcing and regional orographic effects, while air–sea interactions exert a secondary influence on the storm trajectory. In contrast, SST structure plays a substantially larger role in modulating cyclone morphology, convective organisation and precipitation. Mesoscale SST anomalies favour enhanced diabatic activity and more organised convection, whereas their removal leads to a weaker and less coherent precipitation response. Sensitivity experiments further highlight a systematic thermodynamic response to SST changes, while the PGW simulation suggests an amplification of precipitation-producing processes under future climate conditions. Overall, the study highlights the hybrid nature of the event and emphasises how large-scale dynamics govern cyclone evolution, while mesoscale air–sea interactions critically modulate the intensity and hydrological impacts of Mediterranean tropical-like cyclones.

How to cite: Ricchi, A., Sancho-Calvo, C., Serafini, P., Nastasi, M., D'Amico, C., Avolio, E., Ferretti, R., and Miglietta, M. M.: On the Air Sea interaction and Future Climate Sensitivity of a Winter Tropical-Like Cyclone Jolina, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-128, https://doi.org/10.5194/egusphere-plinius19-128, 2026.

As global warming alters atmospheric circulation, the trajectories and intensities of weather systems are shifting, posing severe threats to highly exposed coastal communities. While much attention is given to the Mediterranean area, the adjacent regions of Macaronesia and Western Europe are increasingly vulnerable to cyclones coming from the Atlantic. This study diagnoses the long-term trends and large-scale causalities driving northward trajectories of African Easterly Waves (AEWs), the primary precursors to tropical cyclogenesis in Atlantic basin.

A long data of 84 years of ERA5 reanalysis (1940–2024) is analyzed and an objective tracking algorithm is applied, to isolate a subset of anomalous AEWs (A-AEWs) that deviate from their climatological westward path. To improve the physical understanding of the synoptic-scale atmospheric and oceanic environments that force this early recurvature, these events are compared against a 30-year dynamic climatology.

The analysis reveals that A-AEWs are steered northward by a distinct large-scale configuration. A poleward-displaced and significantly strengthened Azores High, coupled with an enhanced mid-latitude trough over the northeastern Atlantic, disrupts the standard steering flow in the tropical belt. Simultaneously, anomalously warm sea surface temperatures within the wave’s recurving region and substantial modifications in low-level moisture transport act as critical thermodynamic drivers, allowing the incursion of these systems into regions traditionally cooler and with a less favorable environment.

The identified synoptic and oceanic anomalies positively condition the presence of tropical systems in the historically weakly active northeastern Atlantic. By unravelling the causal mechanisms linking large-scale circulation anomalies and regional air-sea variability, this study highlights an increasingly recurrent weather threat and underscores the urgent need for improved monitoring and prediction of these synoptic precursors to protect vulnerable European coasts in a changing climate.

How to cite: Rodríguez Acosta, E. J., Gómez Plasencia, P., González Alemán, J. J., Calvo Sancho, C., Díaz Fernández, J., Bolgiani, P., Luna Rico, M. Y., Montoro Mendoza, A., Martín Pérez, M. L., and Gómara Cardaalliaguet, I.: Synoptic Environments of Northward-Recurving African Easterly Waves: An Emerging Threat for Southwestern Europe, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-59, https://doi.org/10.5194/egusphere-plinius19-59, 2026.

Medicanes (Mediterranean hurricanes) are among the most hazardous high-impact weather systems affecting the Mediterranean basin, producing intense precipitation, severe winds, coastal flooding, and widespread socio-economic impacts in densely populated coastal regions. Recent advances in satellite Earth Observation are progressively transforming the monitoring of these tropical-like cyclones from retrospective classification toward near real-time physical characterization of their lifecycle and tropical-transition processes.

This work presents the near real-time multi-sensor analysis of cyclone Jolina (March 2026), one of the most recent observational examples of medicane, according to the new medicane definition recently included in the glossary of the American Meteorological Society (https://glossary.ametsoc.org/wiki/medicane/). According to this framework, a medicane is defined as a mesoscale Mediterranean cyclone exhibiting a warm core extending into the upper troposphere, spiral cloud bands, an eye-like structure, and a nearly symmetric surface wind circulation with maximum winds concentrated close to the storm center.

Cyclone Jolina originated as a baroclinic disturbance and progressively evolved toward a compact, diabatically driven warm-core system approaching the Libyan coast. Infrared and passive microwave satellite observations revealed the transition from an asymmetric cold-core cyclone to a tropical-like structure characterized by upper-tropospheric warm-core signatures, spiral cloud organization, and enhanced rotational symmetry. Particularly remarkable was the occurrence of this tropical transition during an atypical season and under relatively cold sea surface temperature conditions, highlighting the complex interplay between upper-level dynamics and diabatic processes in medicane development.

The analysis combines geostationary MSG-SEVIRI observations, passive microwave radiometry (e.g., ATMS, AMSU/MHS, as well as the newly available Arctic Weather Satellite and EPS-SG Microwave Sounder), scatterometer-derived ocean surface winds, and Synthetic Aperture Radar (SAR) measurements from Sentinel-1A. Remarkably, near real-time cyclone tracking is provided through the DeMeTra deep-learning algorithm, which estimates the medicane rotational center every 5 minutes using SEVIRI Airmass RGB imagery sequences. Passive microwave observations around the oxygen absorption complex near 55 GHz are exploited to identify upper-tropospheric warm-core anomalies, while humidity sounding channels around 183.31 GHz are used to detect signatures of stratospheric dry-air intrusion and associated potential vorticity anomalies contributing to cyclone intensification and warm-core development.

Beyond its meteorological significance, Jolina also demonstrated the substantial socio-economic relevance of Mediterranean tropical-like cyclones. Severe weather conditions triggered emergency measures across southern Italy and Libya, including school closures, transport disruption, flooding, landslides, evacuations, and even casualties. Interestingly, some of the strongest impacts occurred during the earlier stages of the cyclone, before the complete tropical transition occurred, emphasizing the importance of considering the whole lifecycle and both synoptic-scale interactions and medicane-scale processes in hazard assessment.

This case study demonstrates the increasing capability of integrated multi-sensor Earth Observation systems, combined with artificial intelligence approaches, to identify and monitor medicane formation and tropical transition in near-real time. The methodologies developed within the ESA MEDICANES project provide new opportunities for operational monitoring, early warning, and improved risk assessment of Mediterranean cyclones under changing climatic conditions.

How to cite: Panegrossi, G. and the ESA MEDICANES Project Team: Mediterranean Cyclone Jolina: Near Real-Time Detection of Medicane Formation Using Multi-Sensor Earth Observation, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-45, https://doi.org/10.5194/egusphere-plinius19-45, 2026.

Medicanes are rare Mediterranean tropical-like cyclones characterized by small spatial scales, rapid evolution, and in particular a warm core, a cloud free eye, and a closed ring of strong winds, leading to potentially severe coastal impacts, which require robust near-real-time detection and tracking from high-frequency geostationary satellite imagery. Their automatic detection and tracking remain challenging because labelled events are scarce, cyclone morphology is highly variable, and satellite-based signatures may be confused with other organized cloud systems.

This work presents DeMeTrA, a deep-learning framework for medicane detection and rotation center localization exploting MSG SEVIRI Rapid Scan Service (RSS) Airmass RGB image sequences. The system combines self-supervised spatiotemporal representation learning based on VideoMAE pretrained vision transformer model, with supervised downstream modules for cyclone presence estimation and center tracking. The architecture was developed through a two-scale detection and tracking strategy motivated by subsequent analyses of basin-scale inference. High-resolution video Transformer backbones provide powerful spatiotemporal representations, but their use in this context requires the Mediterranean domain to be processed through fixed-size small local crops compatible with the pretrained input geometry. This local formulation may limit the availability of full-domain spatial context during the initial detection stage. Under realistic Mediterranean conditions, where organized cloud systems, frontal structures, and peripheral spiral-like patterns can resemble medicane signatures, independent local decisions may lead to false alarms or to multiple candidate centers that are not physically consistent at basin scale. To address this limitation, DeMeTrA integrates a lightweight first-pass module operating on the full Mediterranean basin at reduced spatial resolution. This module estimates cyclone presence and provides a coarse cyclone-center location, which is then used to guide the high resolution VideoMAE tracking stage over a physically consistent region of interest. By separating basin-scale event screening from local center refinement, the framework preserves the advantages of pretrained VideoMAE representations while restoring the large-scale contextual information required for robust detection. This two-scale design limits false-alarm generation, avoids inconsistent candidate centers from independent spatial crops, and provides a single coherent center-track estimate for each detected event, supporting near-real-time medicane monitoring from geostationary infrared satellite observations.

Applications of DeMeTra to documented medicane cases will be shown to analysie its capabilities and skills during the storm development and mature phases. The methodology is currently being extended to the MTG Flixible Combined Imager FCI) for future applications.

Keywords: medicanes; MSG SEVIRI; deep learning; vision transformer; cyclone detection; cyclone tracking

How to cite: D'Armiento, D., Sebastianelli, S., D'Adderio, L. P., Sanò, P., Casella, D., and Panegrossi, G.: DeMeTrA: A Two-Stage Coarse-to-Fine Deep Learning Framework for Medicane Detection and Tracking from MSG SEVIRI Image Sequences, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-126, https://doi.org/10.5194/egusphere-plinius19-126, 2026.

The NASA TROPICS (Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats) Earth Venture (EVI-3) mission, was successfully launched into orbit on May 8 and May 25, 2023 (two CubeSats in each of the two launches into 550-km orbits with approximately 33-degree inclination, with swaths extending to almost 40 degrees North and South latitude, thus providing observations of the southern half of the Mediterranean region). Over the course of the mission, TROPICS provided more spaceborne microwave soundings than any operational program, and the combined forecast impact was larger and more spatially coherent than that of any individual passive microwave platform, illustrating the benefit of constellation-based temporal sampling for constraining rapidly evolving tropical convection. Prior to the deorbit of the last TROPICS spacecraft in December 2025, observations of 3-D temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution were used to conduct high-value science investigations of tropical cyclones and other severe weather phenomena. TROPICS has provided rapid-refresh microwave measurements (median refresh rate of better than 60 minutes early in the mission with four functional CubeSats) in twelve channels spanning 92 to 205 GHz over the tropics that can be used to observe the thermodynamics of the troposphere and precipitation structure for storm systems at the mesoscale and synoptic scale over the entire storm lifecycle. Thousands of high-resolution images of tropical cyclones have been captured by the TROPICS mission, revealing detailed structure of the eyewall and surrounding rain bands. The new 205-GHz channel in particular (together with a traditional channel near 92 GHz) has provided new information on the inner storm structure, and, coupled with the relatively frequent revisit and low downlink latency, has informed tropical cyclone analysis at operational centers. The suite of TROPICS products is publicly available with much improved median revisit rates and were provided with data latencies that are sufficient to enable their use in operational tropical cyclone forecasting applications. In this presentation, we highlight the use of these high-revisit thermodynamic data from TROPICS to better characterize storm structure and environmental conditions over a variety of cases over the 30-month mission lifetime.

How to cite: Blackwell, W. and the TROPICS Science Team: New Capabilities for Observing Precipitation Intensity and Structure Provided by the NASA TROPICS Microwave Radiometer Constellation Mission, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-48, https://doi.org/10.5194/egusphere-plinius19-48, 2026.

How to cite: Chandrasekar, C. V., Biswas, S., and Radhakrishnan, C.: A Radar-Based AI Framework for Nowcasting Severe Hailstorms, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-34, https://doi.org/10.5194/egusphere-plinius19-34, 2026.

The Mediterranean region is characterised for its strong spatial and temporal variability in precipitation extremes. Such a variability, driven by complex atmospheric dynamics and intensified by climate change, results in a high exposure to natural hazards, particularly short-duration and high-intensity convective precipitation that usually generate flash floods in small to medium catchments. These phenomena pose significant challenges for precipitation estimation, monitoring, and risk management, especially in highly urbanised or topographically complex catchments.

In October 2024, the eastern Mediterranean coast of Spain was impacted by an extreme meteorological cut-off low associated with intense convective instability and exceptional rainfall accumulations up to 778 mm in 24 h and 79.4 mm in 1 h. The El Poyo Ravine catchment (385 km²) was the most affected area with severe damage to infrastructure, 238 fatalities, 4 500 buildings and 120 000 vehicles. It highlighted the urgent need for reliable methodologies to characterise convective precipitation and support early warning and preventive actions.

This research aims to identify and assess suitable spatial interpolation methods of precipitation for high localised convective storms, with a focus on improving precipitation characterisation for future forecast and operational applications. Based on a comprehensive literature review, eight interpolation methods were selected, including deterministic, geostatistical, and mathematical-formulation-based approaches. Quantitative validation was performed using metrics such as RMSE and the Nash-Sutcliffe Efficiency coefficient between observations and estimates.

The October 2024 flood event in the El Poyo Ravine catchment was selected as case study. Rainfall fields at each time step were generated by using 15-min observations at 12 rain-gauging stations of the real-time system (SAIH) of the Júcar River Basin Authority. Rainfall fields were generated with the eight interpolation methods of precipitation considered in the study.15‑min rainfall observations at 9 rain-gauging stations of the crowdsourced ECOWITT network were used for validation purposes, after undergoing a strict quality control process to discard either poor data or inconsistent stations. The analysed period spanned from 28 October 2024 at 07:00 to 30 October 2024 at 06:45 with a 15‑minute temporal resolution, focusing on the most intense convective phases of the event. Validation considered only time steps with available observations at both networks.

Results show that accuracy and computational cost strongly depend on the interpolation method. While the Inverse Distance Weighting (IDW) method provides results close to observations with low computational cost, local ordinary kriging requires a much higher computational cost to achieve comparable performance. In addition, the mathematical-equation-based method is more suitable for small catchments, as accuracy increases with decreasing catchment size.

Although this exploratory research focuses on a single catchment and one extreme event, the proposed methodology provides a transferable framework that can be applied to additional events and independent datasets. Therefore, this work can contribute to improving precipitation estimation strategies for Mediterranean catchments and supporting more effective hazard monitoring and risk management.

Acknowledgment: This research was supported by INECO (Ingeniería y Economía del Transporte S.M.E. M.P., S.A.) through funding provided under the project ‘Application of stochastic methods for flood assessment in urban areas’. Ángela Zaragoza-Paredes would like to thank the Fundación José
Entrecanales Ibarra for its financial support through a PhD research grant.

How to cite: Zaragoza-Paredes, Á. M., Mediero, L., Fernández-Fidalgo, F. J., and Lama-Pedrosa, B.: Comparison of precipitation interpolation methods applied to the October 2024 extreme rainfall event in Valencia (Spain), 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-18, https://doi.org/10.5194/egusphere-plinius19-18, 2026.

Rainfall detection and monitoring rely heavily on ground observation stations, meteorological radars, and microwave/infrared sensors onboard satellite platforms. However, the irregular distribution of observation stations, radar limitations due to ground clutter and topographic blockage, and the low spatial and temporal resolutions of polar-orbiting satellites—which carry the microwave sensors providing direct precipitation data—complicate rainfall tracking in urban areas during flash floods. To overcome these limitations, there is growing interest in approaches that utilize signal attenuation data from Commercial Microwave Links (CML) within telecommunication networks. Rain-induced attenuation on these CML signals provides critical information for estimating precipitation type and intensity.

This study aims to perform the first CML-based high-resolution rainfall estimation in Türkiye, focusing on İstanbul—a megacity with a population of 16 million, complex micro-climatic features, and high flood vulnerability. The methodological framework integrates signal data from thousands of CML lines operated by Vodafone Türkiye with a network of 45 rain gauges belonging to the Turkish State Meteorological Service (TSMS). The proposed model architecture includes wet-dry classification of signal data, dynamic correction of additional signal losses caused by antenna wetting (wet antenna effect), and optimization of the attenuation-rain rate relationship tailored to local precipitation characteristics. This paper presents the data processing infrastructure, station-based validation methods, and the potential contributions of this pioneering CML-based rainfall retrieval system to the urban hydro-meteorological monitoring capacity of İstanbul.

Keywords: Commercial Microwave Link (CML), Rainfall, İstanbul, Türkiye.

How to cite: Akın, M., Durmaz, A., Öztopal, A., Tekeli, A. E., Öztürk, A., Yilmaz, F., Tatli, Z., Çoban, D., Gül, G., Anit Türkan, S., and Öztopal, Z.: First Implementation of CML-Based Rainfall Estimation in Türkiye: Focus on İstanbul , 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-122, https://doi.org/10.5194/egusphere-plinius19-122, 2026.

Mediterranean environments are characterized by highly intermittent hydro-meteorological
processes, including intense rainfall events, flash floods and rapidly evolving atmospheric
conditions. These phenomena generate considerable forecasting challenges despite recent
advances in Machine Learning (ML), Deep Learning (DL) and foundation models applied to
environmental prediction.
While most studies focus on comparing forecasting algorithms, the intrinsic relationship
between the statistical structure of environmental variables and their forecastability remains
poorly understood. We hypothesize that predictive performance is strongly constrained by
the statistical organization of the observed processes and not solely by model complexity.
To investigate this question, we present SAPHIR DATA SERVICE, a cloud-native en-
vironmental intelligence platform developed at SPE lab, in the University of Corsica in
collaboration with LiSN Lab in the University of Paris Saclay . The platform supports
the continuous acquisition, storage, visualization and exploitation of heterogeneous envi-
ronmental observations originating from meteorological stations, hydrological sensors, IoT
monitoring devices and institutional environmental services.
SAPHIR DATA SERVICE relies on a dual-layer data architecture. A real-time database
supports operational monitoring, environmental surveillance and nowcasting activities, while
a historical database supports long-term analyses, retrospective studies, machine learning
training and scientific investigations. This architecture enables the simultaneous manage-
ment of operational and research-oriented workflows within a unified framework.
The backend infrastructure is continuously supervised through Grafana dashboards pro-
viding real-time monitoring of acquisition pipelines, database services, sensor status and
environmental observations. A complementary web frontend provides access to environmen-
tal indicators, historical analyses, forecasting products and decision-support services.
Beyond data management, the long-term objective of SAPHIR DATA SERVICE is the
implementation of a continuous environmental intelligence pipeline linking observation, in-
gestion, learning, prediction and decision support.
Within this framework, we investigate whether forecastability can be considered an in-
trinsic property of environmental variables and whether it can be explained through their
statistical signatures. To address this question, we introduce a characterization framework
combining temporal autocorrelation, spatial intercorrelation, spatio-temporal structure func-
tions, fractional moments, skewness, kurtosis and intermittency.
These descriptors are evaluated against forecasting performances obtained from a cata-
logue of statistical, machine learning and foundation models, including persistence baselines,
ensemble methods and modern deep-learning architectures.
The Porto-Vecchio study area provides a real-world Mediterranean testbed for evaluat-
ing how environmental statistical signatures relate to achievable forecasting skill within an
operational nowcasting framework. The proposed approach aims to establish a quantitative
relationship between environmental data structure and predictive performance, providing
new perspectives for rare-event forecasting, hydro-meteorological risk management and en-
vironmental decision-support systems.

How to cite: Silvani, X., Duchaud, J.-L., Muzy, J.-F., Paoli, C., and Al Agha, K.: SAPHIR DATA SERVICE: Environmental Forecastability andHydro-Meteorological Nowcasting, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-65, https://doi.org/10.5194/egusphere-plinius19-65, 2026.

This study introduces a network-based framework for characterizing and clustering the spatial organization of drought and wet extreme regimes at multiple accumulation timescales, applied to the 0.5° gridded SPEI Global Drought Monitor dataset over Italy. Extreme events are identified through run theory, extracting a set of statistical descriptors for each pixel and temporal scale: total number and frequency of events, temporal event occurrence fraction, mean and maximum duration, mean and maximum severity, mean and maximum intensity, global and local inter-event temporal irregularity, and the dominant season of event peak occurrence. These descriptors constitute a 12-dimensional feature space, which is transformed into a similarity network using Mahalanobis distance to account for inter-feature correlations. Community detection is then performed via the Louvain algorithm to identify pixel clusters sharing statistically similar extreme regimes. Partition quality is assessed through modularity Q and feature-space silhouette width and validated against a 1,000-sample permutation-based null distribution.

The Louvain algorithm consistently identifies 4 to 6 communities across all temporal scales for both drought and wet events, with all partitions achieving high statistical significance. For drought events, modularity Q exhibits a clear increasing trend at longer accumulation periods, rising monotonically from SPEI-7 to SPEI-12, indicating that community structure becomes progressively more pronounced as the accumulation timescale increases. F-ratio analysis reveals a clear three-phase regime across timescales. At short scales (SPEI-1, SPEI-3, SPEI-5), the dominant season of event peak occurrence governs cluster discrimination, reflecting the strong seasonality of short-term drought events. At intermediate scales (SPEI-6 to SPEI-9), discrimination shifts toward event-structure metrics such as severity and frequency. At long scales (SPEI-10 to SPEI-12), maximum spell severity and duration reach their highest explanatory power, indicating that persistent multi-month drought structures become the dominant axis of spatial differentiation.

For wet events, modularity Q does not exhibit a monotonic trend across scales and remains lower than its drought counterpart at most timescales, suggesting that wet regimes are spatially less structured than drought regimes. The dominant season of event peak occurrence is nearly uninformative for clustering, indicating an absence of seasonally organized differentiation. From SPEI-1 to SPEI-9, cluster discrimination is primarily driven by maximum duration and severity, peaking at SPEI-4 and SPEI-5. A sharp regime shift occurs at longer timescales (SPEI-10 and SPEI-11), where these duration- and severity-based features lose most of their discriminative power, and are replaced by mean intensity and inter-event temporal irregularity, revealing a scale-dependent reorganization of the drivers of spatial heterogeneity in wet spell regimes.

This study, integrating run theory, multi-scale feature extraction, and network-based community detection, provides a statistically robust and transferable framework for characterizing the spatial organization of hydroclimatic extremes, whose scale-dependent and phase-specific clustering structure would remain hidden to conventional single-scale approaches.

How to cite: Telesca, L.: Spatial clustering of drought and wet spell regimes over Italy: a feature-based network approach across multiple SPEI timescales, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-97, https://doi.org/10.5194/egusphere-plinius19-97, 2026.

Mountain regions are particularly vulnerable to climate change, as warming reduces snow and ice reserves, thus amplifying positive temperature feedbacks. These processes also have consequences for the hydrological cycle and, therefore, leading to wide-ranging impacts on society by altering ecosystem services and products. This highlights the importance of understanding how climate change affects mountain areas. However, the limited availability of long-term climate records at high elevations, due to adverse weather conditions, makes high-resolution regional climate models essential for studying complex terrain.

The CIMAs (Climate Research Initiative for Iberian Mountain Areas) project focuses on analyzing climate variability and the impact of climate change on the Central System of the Iberian Peninsula. The studied area is the largest mountain range of the peninsula, reaching 2.592 m at its highest point (Almanzor Peak) and includes surrounding areas with lower altitudes.

CIMAS observational data, gathered from several institutions in Portugal and Spain, was used to assess the accuracy of regional models over the domain of interest. Model simulations were produced with the WRF and HCLIM models spanning the period 1990-2025, using two nested domains at 12 and 4 km resolution and a nestdown strategy to produce a 1 km resolution simulation domain over the Central System. The domains at 4 and 1 km resolution were configured as convection-permitting. Both models were driven by the same boundary conditions provided by the ERA5 reanalysis, which was also used as a reference to evaluate the added value of increased resolution by each regional model. Specifically, temperature and precipitation variability at daily temporal resolution were used to evaluate model output against observations.

Results show how increasing resolution improves the simulation of temperatura and precipitation at high elevations and allows for better understanding of the climatology in complex terrain. The comparison of the WRF and HCLIM temperature simulations with observations highlights differences, mostly in the reproduction of extremes. Regarding the precipitation, 1 km resolution tends to overestimate the total accumulations due to an excess of simulated wet days.

How to cite: Madera Sánchez, S., González Rouco, J. F., García Bustamante, E., Navarro Montesinos, J., Vegas Cañas, C., Rodríguez Guisado, E., Sánchez Perrino, J. C., Prieto Rico, I., Rodríguez Camino, E., Cardoso Tavares, R. M., Greciano Zamorano, E., Cardoso dos Santos, L., and García Pereira, F.: Assessment of temperature and precipitation variability over a complex terrain. Multi-resolution model evaluación., 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-113, https://doi.org/10.5194/egusphere-plinius19-113, 2026.

Climate change impact studies (e.g. hydrology, agriculture, health) systematically require high-resolution meteorological variables. However, these disciplines rarely need the full suite of physical variables resolved by computationally expensive dynamical Regional Climate Models (RCMs). Their primary need lies in obtaining reliable projections and, crucially, a wide diversity of simulations to properly characterize climate uncertainty. To address this challenge, statistical emulation via deep learning emerges as a computationally efficient alternative.

This study proposes the use of UNet-based neural architectures as direct emulators of EURO-CORDEX RCMs for high-resolution temperature (EUR-11). The central research question is highly operational: is it possible to train an emulator using a single historical GCM-RCM pair and rely on its capacity to regionalize future projections driven by Global Climate Models (GCMs) different from the one used during its training?

To answer this, the model undergoes a rigorous generalization test against the CORDEX ensemble. Once the network is trained specifically using the historical MOHC-HadGEM2-ES and DMI-HIRHAM5 pair, the emulator is fed with the boundary conditions of all other GCMs available for the DMI-HIRHAM5 regional model in the European repository. The validation assesses whether the emulator's outputs, when forced by these new GCMs, deviate significantly from the original dynamical CORDEX projections for those exact pairs.

Preliminary results show that the dispersion (uncertainty spread) generated by the emulator's inference ensemble is equivalent to that of the original CORDEX dynamical ensemble. Nevertheless, zero-shot cross-evaluations reveal that the emulator systematically deviates from its dynamical "mirror" pair. These findings help define the viability of using neural networks to generate on-demand climate ensembles, highlighting both their potential for ultra-fast climate variability reproduction and the limitations associated with transfer biases between global models.

Acknowledgements: This work was supported by the ARUBA (PID2023-149080OB-I00/MCIN/EI/10.13039/501100011033), and the INSIEME (FSRM/10.13039/100007801) projects.

How to cite: Pravia-Sarabia, E. and Montávez, J. P.: Rapid emulation of Regional Climate Models via deep learning for impact studies: evaluating inter-GCM generalization, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-77, https://doi.org/10.5194/egusphere-plinius19-77, 2026.

Mediterranean catchments are particularly prone to short-duration, high-intensity rainfall events that generate flash floods with significant impacts. Analyzing this type of event requires sub-daily hydrometric data in order to adequately capture their dynamics. This study investigates trends in flood characteristics across 38 Mediterranean basins in southern France, with an average size of 200km², using hourly discharge, radar rainfall, and reanalysis-derived soil moisture data over the period 1997–2024. Flood events are identified using a peaks-over-threshold approach and classified according to response time (flash-floods versus slower onset floods) and antecedent soil moisture conditions. Trends in flood peaks and direct runoff volumes are assessed using regional quantile regression after applying a spatiotemporal declustering procedure.

Results indicate increasing magnitudes for both flash floods and slow-onset floods under saturated soil conditions. These increases are more pronounced for flood volumes than for peak discharges, with trend magnitudes approximately twice as large. However, these results should be interpreted with caution given the pronounced spatiotemporal variability of flood processes in Mediterranean environments, given that the detected trends are not statistically significant based on a regional bootstrap assessment.

Overall, the results suggests that flood volume provides a more sensitive indicator of change than peak discharge in Mediterranean catchments. This underscores the importance of considering hourly data and process-based flood classification to improve the detection of evolving flood hazards in regions impacted by flash floods.

How to cite: Tramblay, Y., Arnaud, P., and Javelle, P.: Detecting trends in different types of floods in Mediterranean basins using hourly data, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-7, https://doi.org/10.5194/egusphere-plinius19-7, 2026.

Mediterranean agricultural areas may experience abrupt hydroclimatic contrasts, where long dry phases may be followed by concentrated rainfall sequences capable of triggering rapid landscape instability. In these contexts, soil erosion and gully activation are not only the consequence of a single storm, but the result of accumulated climatic and land-surface stressors acting on vulnerable soils. This contribution explores how a sequence of climatic stressors affected a cereal-crop gully system located near Casabermeja, Málaga, southern Spain, an area representative of Mediterranean agricultural landscapes affected by soil degradation, runoff concentration and irregular rainfall regimes. The study focuses on the transition between a markedly dry summer period and a subsequent winter storm train. During June–July 2025, the area received only 2.0 mm of rainfall over 61 days, including a 50-day dry spell. This antecedent dry state was followed by a persistent rainfall sequence between 21 January and 9 February 2026, with 234.8 mm accumulated in 20 days and a daily maximum of 76 mm. This contrast provides a suitable framework to examine how antecedent drought may condition the spatial response of agricultural soils to later rainfall extremes. To assess this response, two high-resolution UAV surveys were acquired before and after the storm sequence. Terrain and multispectral products were used to derive indicators related to topography, surface cover and hydrological organization. These variables were integrated into a machine-learning workflow designed to distinguish pre- and post-event surface conditions and to identify the main spatial controls of the observed response. The results indicate that the post-event pattern was mainly associated with hydrological connectivity and runoff concentration, while vegetation and surface-cover changes played a secondary, modulating role. This suggests that the impact of Mediterranean rainfall extremes depends strongly on the previous climatic state of the landscape and on the degree of soil vulnerability. By framing gully response as the outcome of interacting climatic stressors, this work provides a useful perspective for mapping erosion-prone areas and supporting adaptive soil-management strategies in Mediterranean agricultural environments.

How to cite: Moreno Cuenca, L. and Rodrigo Comino, J.: Climate stressors and hydrogeomorphological instability in Mediterranean agricultural soils: from drought to successive storm rainfall, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-14, https://doi.org/10.5194/egusphere-plinius19-14, 2026.

In literature it is assumed that an extreme is a rare, high (or low) magnitude event, where the concepts of rarity and magnitude depend on
the physical and temporal contexts. A statistical approach is presented to measure and communicate the magnitude of hydrological events and identify extremes. The core of the method is the frequency analysis of time series and the transformation of any data probability distribution into a standard normal distribution, where the event magnitude is expressed by the Z value, which is dimensionless. It provides a probability-based measuring scale that is invariant from the nature and variance of the hydrological phenomena and the spatial context. The Z value has the same properties as standardized indices, such as the well-known Standardized Precipitation Index (SPI), used in drought monitoring. An “extreme” is defined as an event with magnitude Z ≥ 2 (upper tail) or ≤ –2 (lower tail), depending on the nature of the hydrological variable.

The “extreme event” definition proposed does not contain any details about the event’s impact on the ground surface. These impacts depend on both the event magnitude (e.g., rainfall intensity) and land use or anthropogenic modifications of the natural environment as well. Furthermore, any geomorphological and hydrological processes, such as landslides and floods, depend on additional hydrological factors, including the pre-event wetness conditions of the soil, which could dump or amplify the event impact on the ground surface. Thus, the association between the Z value (event magnitude) and its impacts on the Earth surface could not be direct.  

The Z value would provide a more suitable representation of the event magnitude than return period, commonly adopted to express the rarity or exceptionality of hydrological phenomena, as it represents a more stable scale, especially in the tails of the distribution. However, its use does not reduce intrinsic uncertainty and complexity of the probablity model.

How to cite: Leone, G. and Fiorillo, F.: A new classification of the magnitude of hydrological events and extremes using the Z value, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-11, https://doi.org/10.5194/egusphere-plinius19-11, 2026.

Flood frequency estimates derived exclusively from local discharge records are strongly influenced by limited sample sizes and by the extrapolation of the upper tail, which can result in unrealistically discharge quantiles. The framework of the design storm paradigm is too simplistic compared with the actual spatio-temporal variability of precipitation and hydrological processes. The catastrophic October 2024 flood in southern Valencia Metropolitan Area (Spain) offers a unique opportunity to revisit flood frequency analysis under such conditions.

To address these issues, the present study integrates regional precipitation analysis, stochastic weather generation, and distributed hydrological modelling. , the proposed approach better constrains the range and frequency of rainfall-runoff conditions capable of producing extreme flows.

As a consequence, discharge magnitudes previously associated with very long return periods are shown to occur more frequently, implying lower discharge values for a given return period and a higher effective frequency of potentially damaging flows. At the same time, we found a significant difference between the return period of the precipitation of the 2024 event (above a 2,000 years), the flows generated in some tributaries (below 500 years) and that of the main inundation (around 1,000 years).

How to cite: Francés, F., Aranda, J. Á., and Beneyto, C.: The flood frequency analysis of the catastrophic flash flood event of October 2024 in southern Valencia, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-134, https://doi.org/10.5194/egusphere-plinius19-134, 2026.

The AMARNA Platform contains a catalogue of 12,000 episodes of adverse meteorological conditions in Spain, covering the last 1,000 years. This enables studies to be carried out on flood events, covering not only current episodes but also those of greater severity and lower frequency that have occurred in climatic and historical contexts different from the present day.

            This study aims to assess the most severe flood episodes to have occurred in Spain over the last 750 years (1275-2025). For this purpose, the available records identify up to 5,438 episodes in which some type of flood occurred, whether caused by rain, rivers or tides. An initial selection of episodes focused on those that resulted in at least one case of river overflow leading to the complete destruction of a building or infrastructure (including houses, bridges, water mills, dams or canals) and that led to evacuations, rescues, injuries or fatalities. This resulted in 271 episodes.

            For these events, composite indices are derived by weighting the values of certain numerical variables: the structural impact index, the human impact index, the number of affected river basins, and the density of overflow records comprising the event. A list of 53 major events is compiled, to which two different weighting schemes are applied: one emphasising the structural impact component and the other the human impact.

            The results provide a continuous historical overview of the severity of the various episodes, highlighting that those with the greatest structural impact occur during climatic fluctuations already recognised during the Little Ice Age for their high frequency of such phenomena. Whereas since the second half of the 20th Century, the severe episodes that have occurred, including the late October 2024 Valencia area episode, have had a greater impact on people than on buildings and infrastructures. This well-documented divergence may contribute to our understanding of mechanisms for the prevention and management of such emergencies. However, it also highlights that, on a historical scale, episodes with significant destructive potential have occurred and could recur in the current context, with a substantially increased population and similarly high levels of vulnerability.

Acknowledgements:

The authors acknowledge the grants from FLOODMED (PID2024-157662OB-C22), funded by the Spanish Ministry of Science, Innovation and Universities (MICIU/AEI/10.13039/501100011033) and by ERDF/EU.

How to cite: Barriendos, M., Barriendos, J., Gil-Guirado, S., Pérez-Morales, A., and Pino, D.: Study of major flood events in Spain over the last 750 years, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-67, https://doi.org/10.5194/egusphere-plinius19-67, 2026.

Mediterranean extreme weather events are often characterized by intense rainfall over short time periods and rapid hydrological response, making the short-term river water-level prediction a crucial component of flood early warning. In this work, we present the development and the pilot application of a data-driven operational prediction system for river water-level in multiple points in the region of Thessaly, Greece, based on artificial intelligence techniques.

The system exploits high temporal resolution observations from a regional network of meteorological and hydrometeorological stations in Thessaly, Greece, combining past rainfall data with river water-level data over a five-year period. The framework is designed to learn the nonlinear relationship between the antecedent rainfall and the subsequent evolution of the river stage (hydrological response). Several artificial-intelligence models, including gradient boosting machines and neural networks, are trained and evaluated to provide short-term water lever predictions at selected points of the network, with a prediction horizon up to 12 hours.

The preliminary results highlight the potential of artificial-intelligence techniques to real-time flood prediction in Mediterranean environments, providing valuable lead time for the local authorities and improved flood-risk preparedness.

Keywords: early warning systems, rainfall, river water level prediction, artificial intelligence

How to cite: Giannaklis, C.-P., Lagouvardos, K., Kotroni, V., Dimitriou, E., Papadopoulos, A., and Giannaros, C.: An Artificial-Intelligence-based application for short-term river water-level prediction and flood early warning in Thessaly, Greece. , 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-28, https://doi.org/10.5194/egusphere-plinius19-28, 2026.

Rapid urbanization, aging drainage infrastructure, and increasingly heavy rainstorm events have made urban pluvial flooding a major problem for modern cities. Urban planning, risk assessment, and mitigation strategy design all depend on accurate modeling of these types of floods. However, the quality of the input data, especially the topographic information controlling overland flow and the depiction of drainage networks, has a significant impact on the model's effectiveness. Despite their acknowledged significance, these kinds of input data are frequently chosen based more on availability than on a methodical assessment, which could result in inaccurate flood forecasts.

This study examines how preprocessing and input data quality affect urban pluvial flood simulations, with a focus on 1D–2D coupled modeling.
The interactions between subterranean drainage systems and overland runoff are explicitly represented using an integrated framework that combines SWMM for one-dimensional (1D) drainage dynamics and IBER for two-dimensional (2D) surface flow. The study develops a fully coupled 1D–2D IBER–SWMM framework to overcome the drawbacks of purely 2D simulations, allowing dynamic and bidirectional water exchange between the surface and the drainage network. Municipal datasets were used to obtain inlet locations and typologies.

The 1.43 km² study area is a heavily populated part of the Sampierdarena district that is regularly impacted by pluvial floods brought on by rainfall events with very short return periods (3 years).

All things considered, this study highlights the crucial significance of methodical terrain data selection and preprocessing in 1D–2D coupled urban flood models. The fundamental methodological development that improves the physical consistency of surface–subsurface interactions and boosts predictive reliability is the merging of IBER and SWMM. The study offers a structured framework for more transparent and reliable urban flood simulations by clearly quantifying the impact of topographic data attributes on hydrodynamic outcomes. In light of growing hydrological extremes, our contribution promotes robust and data-driven urban flood risk management, supporting both scientific advancement and practical decision-making.

How to cite: Boni, G., Acquilino, M., Gnecco, I., Palla, A., Russo, B., and Sanz Ramos, M.: Impact of preprocessing and input data quality on urban pluvial flood simulations, with focus on 1D–2D coupled modelling. The case of Sampierdarena district of Genova using Iber-SWMM, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-102, https://doi.org/10.5194/egusphere-plinius19-102, 2026.

This study assesses coastal flood exposure and direct economic damages associated with 100-year return-period extreme sea-level events in five vulnerable Spanish coastal hotspots: the Ebro Delta, Alcudia Bay, the Albufera of Valencia, the Mar Menor and Doñana. The analysis considers two time horizons, 2050 and 2100, and two climate change scenarios, RCP 4.5 and RCP 8.5, using high-resolution geospatial flood layers, land-use information and projected land-use change scenarios.

The methodology combines GIS-based spatial analysis, land-use change modelling with MOLUSCE, and depth–damage functions adapted to Spanish land-use categories. Flooded areas were quantified by land use and study area, while direct economic damages were estimated for the modelled flood footprint of each 100-year extreme sea-level scenario. These estimates were calculated for both current land uses and future land-use projections. In addition, potentially developable urban land exposed to coastal flooding was identified to support territorial planning and adaptation strategies.

Results show a strong increase in exposure towards the end of the century. Total flooded area rises from 4,926 ha under RCP 4.5 in 2050 to 28,915.3 ha under RCP 8.5 in 2100. The most affected land uses are rice fields and coastal lagoons, followed by marshes, salt flats and beaches. Event-based direct economic damages for current land uses increase from €109.2 million in 2050 under RCP 4.5 to €808.8 million in 2100 under RCP 8.5, while future land-use projections raise potential damages to more than €1.0 billion in the most severe scenario. The Ebro Delta and the Albufera of Valencia concentrate the largest flooded areas, whereas urban and tourist-related land uses drive the highest estimated economic losses in the Mar Menor and Alcudia Bay, highlighting the key role of urban exposure in determining local economic vulnerability.

The authors gratefully acknowledge the support and funding received from project 22697/PI/24 (ISANMAR), funded by FSRM/10.13039/100007801. This work was also supported by the SHIELD project, funded through the EUniWell Well-Being Research Incubator Programme and Seed Funding Programme of the EUniWell Consortium (European Universities for Well-Being, https://www.euniwell.eu/), within the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No. 101035821.

How to cite: Amor Amor, J. F., Mirete Hernandez, J., Gil-Guirado, S., and Montavez, J. P.: Event-based assessment of coastal flood damages under 100-year extreme sea-level scenarios in Spanish coastal hotspots, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-79, https://doi.org/10.5194/egusphere-plinius19-79, 2026.

Braided rivers constitute fluvial systems of high morphological complexity and significant geomorphological
dynamism. This study analyses the morphological dynamics and braiding intensity of the San Carlo reach
of the Fiumara Amendolea for the period 2022–2024. The Fiumara presents optimal characteristics for the
development of the braiding model: it is a short, steep, ephemeral and torrential watercourse with scarce riparian
vegetation. The analysis of braided systems, such as the one studied here, is key in the context of climate
change, where an increase in the frequency of extreme precipitation events is expected. For the analysed period,
a simplification of the network is observed, a phenomenon that can be attributed to torrential precipitation
episodes recorded during the study period. The methodology integrates photogrammetric processing using
Structure from Motion (SfM) of multispectral UAV/RPAS surveys, GIS-based spatial analysis, and automated
channel network extraction using RivGraph. To measure braiding intensity, four braiding indices (BI) —Brice,
Germanoski-Schumm, Mosley, and the Entropic Braiding Index (eBI; Tejedor et al., 2022)— were computed
for each sub-reach of both the full channel and the most active reach. Additionally, a series of morphological
indices and variables were calculated to establish correlation relationships with the BIs, in order to determine
which of these is most representative of the spatial reality of the Fiumara Amendolea. The results reveal a
generalised reduction pattern in braiding intensity over the analysed period, with alternation of the dominant
geomorphological process; in the headward sector of the San Carlo reach, sedimentation prevails, whereas
incision dominates downstream.
Keywords: braided channels, BI, eBI, Amendolea Fiumara, fluvial geomorphology, SfM photogrammetry,
multitemporal analysis.

How to cite: Bellido Solano, Á., Foti, G., Bombino, G., Pérez Cutillas, P., and Conesa García, C.: Morphological change indicators in a semi-arid braided system, the Fiumara Amendolea (Calabria, Italy): multi-temporal evaluation and analysis, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-114, https://doi.org/10.5194/egusphere-plinius19-114, 2026.

Floods and flash floods are among the most damaging hydrometeorological hazards in the Mediterranean, with impacts shaped by rainfall hazard, exposure, and local susceptibility. This study examines rainfall and local geospatial characteristics associated with documented flood impacts in Greece during 2000–2025 and explores how these characteristics vary by impact severity. The analysis is based on more than 450 flood-related events recorded in the High-Impact Weather Events Database for Greece (HIWE-DB), developed and maintained by the METEO unit of the National Observatory of Athens. The original event reports were systematically reviewed to extract reported affected settlements and localities, yielding approximately 1,700 local impact records. The HIWE-DB impact severity classification was attributed to these local records. Rainfall was extracted from a gridded precipitation dataset with 1 km × 1 km spatial resolution, developed by the METEO unit using observations from its dense surface weather station network across Greece. Two rainfall indicators were calculated for each affected location: precipitation on the day of the reported impact (R24) and accumulated precipitation over the previous day and the day of impact (R48). In addition to this rainfall dataset, rainfall from the MSWEP dataset was also used to estimate the same indicators as a secondary reference to explore how rainfall-product choice may affect the interpretation of impact-generating events. Descriptive and exploratory statistics are used to examine rainfall distributions, selected geospatial and exposure-related indicators, spatial patterns, and relationships with impact severity. The study provides evidence on the local conditions associated with damaging floods in Greece and can inform flood risk assessment, preventive strategies, impact-based warning approaches, and adaptation planning in Mediterranean environments.

How to cite: Papagiannaki, K., Lagouvardos, K., Kotroni, V., and Kyriakou, P.: Assessing rainfall hazard and local factors associated with societal flood impacts in Greece, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-24, https://doi.org/10.5194/egusphere-plinius19-24, 2026.

Flood risk in Mediterranean basins is usually discussed in relation to heavy rainfall and hydroclimatic extremes. However, the damage caused by floods is not only the result of the physical event itself. It is also shaped by the way societies have occupied flood-prone areas over time. This contribution presents preliminary results for the Segura River Basin District, in south-eastern Spain, where a long history of floods coexists with intense urbanisation, especially since the second half of the twentieth century.

The analysis is based on AMARNA, a multidisciplinary database for natural risk analysis that allows flood episodes and municipal flood cases to be reconstructed from historical, documentary, bibliographic and press sources. For the Segura basin, 664 rainfall episodes and 2,042 municipal flood cases have been identified between 1258 and 2025. Each case is classified according to hydrological behaviour, damage to infrastructure and human vulnerability. This makes it possible to compare very different historical periods and to move from a simple list of events to a more systematic interpretation of flood impacts.

In order to explore the relationship between floods and territorial exposure, the paper develops a preliminary Flood Impact and Exposure Index for the period 1900–2025. The index combines two types of information. On the one hand, it uses the AMARNA scores related to infrastructure damage and human vulnerability as an indicator of recorded impact. On the other hand, it incorporates exposure through cadastral data on the age and use of buildings, official flood-prone areas for the 10-, 100- and 500-year return periods, and population data where available. The purpose of the index is not to model hydraulic hazard, but to identify municipalities where flood impacts have become more relevant because urban growth has placed more buildings, people and activities in areas historically exposed to flooding.

The preliminary results show a complex temporal pattern. Over the full historical series, the number of recorded flood episodes increases. However, since 1900 this trend becomes less clear, while the number of affected municipalities per episode and the accumulated impact scores tend to rise, particularly after 1960. This suggests that recent flood impacts cannot be explained only by changes in rainfall. Long-standing inland hotspots such as Murcia, Orihuela, Lorca, Cartagena and Caravaca remain important, but the geography of recent impacts points to a growing concentration in coastal and peri-coastal municipalities, especially around the Mar Menor and in urbanised areas crossed by ramblas, ephemeral channels and alluvial fans.

These findings support the idea that flood risk in the Segura basin has increasingly been amplified by exposure. The expansion of tourist-residential development and other urban uses within flood-prone areas has contributed to a process of coastalisation of risk. The results also raise a broader question for adaptation policies: structural flood defence and channel modification may reduce local hazard, but they can also encourage further occupation of dangerous areas. The proposed historical-GIS approach can therefore help identify exposure tipping points and support spatial planning, disaster risk reduction and climate adaptation in Mediterranean basins.

How to cite: Pérez-Morales, A., Rebotier, J., Barriendos, J., Gomariz-Castillo, F. J., García-Martín, F. M., Ochoa-Rego, J., Carrillo, J. M., Jiménez-Guerrero, P., Pino-González, D., Barriendos, M., Hernández-Hernández, M., and Olcina-Cantos, J.: From flood chronologies to exposure tipping points: preliminary evidence from the Segura River Basin District, SE Spain, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-63, https://doi.org/10.5194/egusphere-plinius19-63, 2026.

This contribution presents the recently published version 2.0 of the Database of Flood Fatalities in the Euro-Mediterranean Region (FFEM-DB 2.0), a multinational dataset documenting 3,737 flood-related fatalities that occurred between 1980 and 2024 across 16 territories (12 corresponding to entire countries). The new release significantly extends the spatial and temporal coverage of the previous version, updating records through December 31, 2024, incorporating four additional study areas, and introducing an event identifier that enables event-based analyses and comparability with international disaster databases.

Key results derived from FFEM-DB 2.0 are presented with a focus on the main variables collected, including victims’ demographic characteristics, accident locations, and circumstances of fatal events. The standardized and harmonized structure of the database allows for consistent cross-regional analyses at the scale of Local Administrative Units, supporting the identification of recurrent patterns and differences in flood mortality across the Euro-Mediterranean region.

Particular attention is devoted to future developments of the database. Ongoing efforts aim at both continuous temporal updating and further geographical expansion to additional territories. Furthermore, new perspectives include the integration of emerging digital archives and the systematic exploitation of heterogeneous data sources available for the last two decades, such as online news repositories and institutional records. In this context, artificial intelligence techniques as natural language processing and automated information extraction, are expected to play a key role in improving data collection, enhancing completeness, and accelerating database updates. Owing to its open and scalable structure, FFEM-DB is therefore positioned as an evolving framework for advancing research and monitoring flood-related mortality in Europe and beyond.

How to cite: Petrucci, O. and the FFEM Team: FFEM, the dataset of flood fatalities in the Euro-Mediterranean Region (1980-2024): results and perspectives, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-54, https://doi.org/10.5194/egusphere-plinius19-54, 2026.

While flood impacts are traditionally measured through the economic data provided by international insurance companies, recent research has shifted toward documenting disaster-related mortality as a crucial indicator of vulnerability and a tool for assessing prevention efforts. Although this mortality has been extensively studied in Europe, it remains poorly documented in North Africa, a region characterized by significant exposure to hydrometeorological hazards. To address this gap, the FFNA (Flood-related Fatalities in Northern Africa) database provides a georeferenced analysis of fatalities across Morocco, Algeria, and Tunisia from 1980 to 2022. This tool aims to improve risk assessment by highlighting the critical influence of behavioral factors and mobility on fatal outcomes. Built according to international FFEM standards, the database compiles 4,054 fatalities from diverse sources—including scientific literature, institutional reports, and press archives—all verified on field  through systematic cross-validation. The findings reveal that flood mortality is predominantly male and closely linked to mobility, with more than half of the deaths occurring in traffic-related circumstances. Week-end are more fatal days with 54 % of mortality on Saturday, Sunday and Monday mostly due to road mobility. As a notable difference from Euro-Mediterranean patterns, deaths inside buildings are less frequent, while electrocutions and wadi crossings emerge as distinctive regional features. Spatial analysis indicates that while the majority of fatalities are concentrated in major urban centers, mortality rates are actually higher in sparsely populated areas where people settle along ephemeral riverbeds (wadis) with limited access to warning systems. Temporally, the majority of deaths occur between August and November, with a slight downward trend in annual mortality since 2010 that may reflect improved risk management. Furthermore, an event-based approach shows a decrease in the average number of deaths per event, but an increase in the number of fatal events resulting from growing urbanization in North Africa. Ultimately, this study offers the first harmonized empirical basis for understanding flood mortality in a region where demographic, urban, and hydro-climatic dynamics differ significantly from other Mediterranean areas.

How to cite: Vinet, F., Tramblay, Y., Raclot, D., Mahé, G., Fehri, N., El Mehdi Saidi, M., Boutaghane, H., and Boulmaiz, T.: Flood related mortality in North Africa : first outcomes of a new comprehensive database, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-8, https://doi.org/10.5194/egusphere-plinius19-8, 2026.

Flood events are among the most widespread natural hazards in France and are responsible for significant damage each year. Although public safety remains a priority, socio-economic impact is emphasised in risk prevention. The purpose is to focus on human vulnerability, through fatality, as an index for evaluating public policies. Based on previous research focused on the French Mediterranean region (BD Vinct-In see Vinet et al., 2022; Boissier, 2013), and within the framework of the EUropean Flood Fatalities named database (Petrucci et al., 2019; Papagiannaki et al. 2022), the study, as part of the FORESEE research project, seeks to extend data collection to mainland France and Corsica over the period 1980–2025. This database enables spatial analysis and temporal distribution of fatalities related to various historical flood events that have occurred across the territory. The scope includes flash floods (in Mediterranean and mountain regions), marine flooding, river floods, urban runoff, and tsunami. It also highlights geographical dynamics of different types of flooding (catchment area characteristics, temporal patterns), while allowing comparisons between fatalities seasonality, intense pluvio-hydrological events occurrence, and the effectiveness of public policies in risk management (river monitoring, weather alert, risk awareness, etc.). Finally, it provides insights into victim profiles, circumstances and locations of death, behaviours, as well as the evolution of human vulnerability over time and space.

How to cite: Nardon, E. and Vinet, F.: Flood related mortality in France over the period 1980-2025, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-9, https://doi.org/10.5194/egusphere-plinius19-9, 2026.

Extreme weather events generate effects that transcend the physical realm, producing economic, social, and political consequences whose magnitude depends both on the intensity of the phenomenon and on the exposure and vulnerability of the affected societies. The literature has identified various mechanisms through which these events can alter social dynamics and collective behaviors, including political responses associated with society's perception of institutional risk management and its impacts (Burke, Hsiang, and Miguel, 2015). In this context, analyzing political responses to extreme events provides a way to understand the adaptive capacity and institutional resilience of exposed territories.

This study analyzes the relationship between flooding episodes and changes in electoral outcomes in municipalities along the Spanish Mediterranean coast. This area is a particularly relevant case study because it has been the site of numerous episodes of intense rainfall that have resulted in serious human and material consequences. Additionally, it is characterized by a high concentration of population and infrastructure, and a complex territorial organization, increases exposure and vulnerability to these types of events.

Based on the integration of databases on floods and electoral results, this study examines: (1) the possible relationship between precursor variables linked to flood events and variables of electoral response; (2) the differences in electoral changes according to political blocs; and (3) the spatiotemporal variability of these effects among autonomous communities. Furthermore, the analysis incorporates a multi-level perspective, in order to assess whether the political attribution of the impact varies according to the institutional scale and the distribution of powers in areas such as territorial planning, civil protection, water management or emergency response.

Results suggest that the temporal proximity between the occurrence of a flood and the holding of elections is associated with greater variation in electoral results, which points to a greater sensitivity of electoral behavior to recent events. This response would not be homogeneous between political options, observing differentiated electoral effects between blocks. However, the power/opposition effect seems to be more relevant. Likewise, it is expected that there will be spatial heterogeneity in the electoral response between autonomous communities, depending on their institutional, social characteristics and political context.

How to cite: García Fernández, E., Gil-Guirado, S., Jiménez-Guerrero, P., and Montávez, J. P.: The political attribution of risk: floods and election results, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-75, https://doi.org/10.5194/egusphere-plinius19-75, 2026.

One of the key lessons learned from the catastrophic floods that occurred on October 29, 2024, and caused 238 deaths in Spain, was the need to raise public awareness about flooding, both to improve prevention and to enhance emergency response (Llasat, 2024). In this vein, years ago the GAMA group at the University of Barcelona (UB) developed a free mobile app (FLOODUP) to be used as a citizen science tool, allowing the public to submit observations about floods—both in real time and from the past—as well as bad practices or risk mitigation measures (Llasat-Botija et al., 2025). The app also includes explanations to improve users’ flood risk awareness; it can be used anywhere in the world and is available in Spanish, Catalan, Basque, English, and French.

The “In the Footsteps of Water” project, led by the General Directorate of Water under the Ministry for Ecological Transition and Demographic Challenge, was launched in response to the 2024 floods with the aim of promoting civil society participation in improving understanding of flood risk. To this end, it was decided to use the FLOODUP app, which was adjusted for the project. The campaign, which is still ongoing, involves submitting photographs of historical floodwater marks, accompanied by information on their location, the height of the mark, and the event itself. It also includes questions about the flood risk perception of the citizen submitting the images. The campaign has developed educational materials, individual worksheets, and worksheets to promote group participation, which can be found at https://www.miteco.gob.es/es/agua/temas/gestion-de-los-riesgos-de-inundacion/cnih/tras-huellas-agua.html.

Participation in the project helps preserve historical memory and shows the citizens how high a flood can rise. At the same time, as regards its citizen science component, the project aims to incorporate the information gathered into the cartography of flood-prone areas.

Llasat, M.C., 2024. Spain’s flash floods reveal a desperate need for improved mitigation efforts. Nature, WORLD VIEW, 26 November 2024 Nature 635, 787 (2024). doi: https://doi.org/10.1038/d41586-024-03825-0.

Llasat-Botija, M., L. Esbrí, T. Rigo, M.C. Llasat, 2025. The Application of Citizen Science to Evaluate the Emergency and the Response of the Population in the October 2019 Flash Flood Event in the Francolí River (NE Spain). Water 2025, 17, 610. https://doi.org/10.3390/w17050610

How to cite: Llasat, M.-C., Llasat-Botija, M., Aroca-Jiménez, E., and Sánchez Martínez, F. J.: In the footsteps of Water, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-87, https://doi.org/10.5194/egusphere-plinius19-87, 2026.

The presentation focuses on the interplay between uncertainty in probabilistic forecasts and uncertainty in public response for an impeding impactful flood event. Exaggeration of the frequency and magnitude of impactful events under the current climate variability and change make this analysis important for improved response and adaptation for the forecast and disaster management agencies worldwide.

The theoretical work is based on relationships obtained from surveys of communities in the United States and on established error characterizations of probabilistic forecasts of impactful event occurrence. The focus of the analysis is to estimate the most effective time to issue evacuation statements for a forecast, impeding impactful event. The methodology allows for adaptive estimation in real time. The work is based on the formulation of Georgakakos (2025) with extensions on the characterization of uncertainty.  It combines decision theory solutions embedded within ensemble Monte Carlo simulations to characterize uncertainty.  Time is normalized to allow for a wide range of forecast lead times and event occurrence times from present time.  The following Figure, adopted from the reference mentioned, indicates the component processes considered.

Open Access Reference: https://doi.org/10.1007/s11069-025-07540-5

Initial results highlight the importance of the time to complete the evacuation and the threshold of probability set by the agencies for action on the timing decision for evacuation statement. Higher time specificity of the forecast probability of occurrence of the impeding event allows for longer times from present for issuing the evacuation statement. As the time of event impact nears with non-negligible occurrence probability at the decision time, higher risk aversion (using high percentile of the decision function versus using expected value of that function) shortens the time to issue the evacuation statement.

How to cite: Georgakakos, K.: Incorporating Forecast and Public Response Uncertainty in Agency Timing Decisions for Evacuation Statements, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-85, https://doi.org/10.5194/egusphere-plinius19-85, 2026.

Under climate change, semi-arid Mediterranean regions such as the Quípar basin (SE Spain) are increasingly exposed to the combined risks of floods and droughts, further exacerbated by land-use changes. Addressing these interconnected hydroclimatic extremes requires integrated, catchment-scale strategies that combine biophysical effectiveness with social acceptability. This study presents a participatory co-design process to develop contrasting climate adaptation scenarios in the Quípar basin, combining Nature-based Solutions (NbS) and grey infrastructure. The ultimate aim is to enhance stakeholder understanding of local and regional impacts and support the selection of effective adaptation pathways.

Through semi-structured interviews, 35 stakeholders from key sectors (farmers, policymakers, NGOs, researchers, and local communities) were engaged to identify flood and drought hotspots, perceived drivers of hydroclimatic risk, and existing and potential adaptation measures. Stakeholders also assessed their preferences, spatial suitability, and key barriers to implementation. In total, 54 land-based measures were identified, including 34 NbS and 20 grey infrastructure measures (21 addressing both floods and droughts, 9 targeting floods only, and 4 droughts only). The most widely supported measures included ground cover practices, reforestation, and terracing. The main flood hotspot was consistently located in the middle reach of the Quípar River, while drought risk was perceived as affecting the entire catchment. Key perceived drivers of increasing hydroclimatic risk included climate change, land-use change, and shifts in agricultural practices, while major perceived barriers to implementation were limited social awareness, economic constraints, and bureaucratic complexity.

Building on these results, two co-design workshops (n = 35) were conducted to develop three contrasting adaptation scenarios based on the Shared Socioeconomic Pathways (SSPs): (i) an NbS-oriented scenario (SSP1), (ii) a business-as-usual scenario combining NbS and grey infrastructure (SSP2), and (iii) a technology-driven scenario focused on grey infrastructure (SSP5). Participants collaboratively prioritised and spatially allocated adaptation measures, fostering integrated spatial thinking, social learning, and awareness of synergies and trade-offs.

Although the three scenarios differ in their chosen measures, several functions overlap: all address flood-prone areas through targeted interventions; river and floodplain restoration in the NbS scenario, channelisation in the technological scenario, and vegetation clearance in the business-as-usual scenario. Upstream water retention is promoted through ponds and landscape features in the NbS scenario, and through check dams in the technological and business-as-usual scenarios. Similarly, aquifer recharge is enhanced through wetlands in the NbS scenario and through managed infiltration in the technological scenario.The scenarios also diverge: the NbS scenario prioritises reducing water demand and restoring vegetation (reforestation, cover crops, pastoralism), the technological scenario focuses on increasing water supply through infrastructure (reservoirs, water transfers, desalination, wastewater reuse, expanded drip irrigation), while the business-as-usual scenario occupies an intermediate position, with practices such as grazing, drought-tolerant crops, and swales without substantially reducing irrigation or enhancing vegetation cover. 

In a next phase, the impacts of these scenarios will be quantified using hydrological modelling to assess their performance under current and future climate conditions. Model results will be shared and discussed with the stakeholder groups to further support integrated spatial planning for effective climate adaptation.

How to cite: Bosch, C., de Vente, J., and Eekhout, J.: Participatory co-design of climate adaptation scenarios for flood and drought mitigation in a semi-arid Mediterranean catchment, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-93, https://doi.org/10.5194/egusphere-plinius19-93, 2026.

This work analyzes Tropical Storm Delta (2005), its extratropical transition and its associated impacts, had it developed over ocean temperatures 2 ºC higher than those given, characteristics of a warmer future climate. The focus will be on the impacts of the cyclone on the Canary Islands (Spain) and how they would change in this scenario due to the influence of warmer sea surface temperatures (SSTs). To this end, two simulations performed with the high-resolution HARMONIE-AROME model are considered: a control simulation based on initial and boundary conditions from the ERA5 reanalysis, and a warm simulation where a disturbance of +2 ºC is added to the SSTs. The economic impact is studied employing data from the Spanish Insurance Compensation Consortium and following their official criterion to consider regions at risk due to atypical cyclonic storms. The results show that Delta becomes a deeper and more intense cyclone in the warmer scenario, reaching hurricane status. Consequently, its extratropical transition becomes a much more severe phenomenon, with a significantly greater impact on the Canary Islands. This occurs in the type of precipitation, coastal impacts, and especially strong wind gusts, which cause a 29% increase in the potential economic losses due to Delta. These results are particularly relevant, since they quantify the increase in economic damage caused by a tropical cyclone due to the oceanic warming projected in future scenarios.

How to cite: Gómez-Plasencia, P., Rodríguez-Acosta, E. J., González-Alemán, J. J., Calvo-Sancho, C., Díaz-Fernández, J., Montoro-Mendoza, A., Bolgiani, P., Martín, M. L., and Gómara, Í.: Potential impacts of Tropical Storm Delta in the Canary Islands under warmer ocean conditions, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-58, https://doi.org/10.5194/egusphere-plinius19-58, 2026.

Many studies have examined flood-related mortality in many climatic contexts (USA, Australia, Mediterranean regions, etc.). While tropical cyclones have also been the subject of epidemiological studies, a gap remains on the wind-related fatalities in Europe despite the existence of fairly general databases (EM-DAT). Despite the significant human impact of these phenomena, data remains fragmented and scattered across press archives, institutional reports, and specific databases. A study conducted as part of a Foresee research project addresses the victims linked to wind phenomena. Following the FFEM DB protocol (Petrucci et al., 2019), a comprehensive database of wind-related deaths in France for the period 1980-2025 has been built including fatalities caused by windstorms, tornadoes, thunderstorm gusts, and episodes of heavy swell. For each fatality, the DB addresses the circumstances of the deaths and identifies vulnerability factors. The database also put together variables related to the spatio-temporal context, individual profile, and circumstances of the incident (time, location, etc.). The presentation aims at presenting a first statistical analysis of this database to highlight the highest-risk situations and their evolution over time. It helps to better identify the most exposed populations, frequent patterns of mortality, and to define prone areas and the seasonality of wind phenomena.

How to cite: Le Golvan, A. and Vinet, F.: First results from a wind-related fatalities French national database over the period 1980-2025, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-10, https://doi.org/10.5194/egusphere-plinius19-10, 2026.

In the near future, wind and solar generation are projected to play a key role in Europe's energy sector. An example is the Spanish roadmap to produce around 80% of its electricity from renewables by 2030, dominated by both sources.

 However, the transition to these envisioned renewable power systems poses a formidable challenge. For instance, with the rising share of variable renewable energy, the power system becomes increasingly vulnerable during periods of very low renewable energy production ("energy droughts") or very high load demand. Specific weather patterns may give rise to so-called compound extreme events, characterized by the simultaneous occurrence of several hazards, such as a scarcity of solar and/or wind resources combined with high load demand. The occurrence of these events and the response of the power system must be carefully evaluated to optimally define mitigation and adaptation strategies. Despite the importance of this issue, there is no consensus on the definition and identification procedures for extreme events.

In this work, the occurrence of solar PV, wind and compound solar PV and wind energy drought events in Spain is analyzed using a novel identification procedure, based on the SPA algorithm. This procedure accounts for the high seasonal variability of the renewable resources in the study region. The study is conducted on a daily basis, using SHIRENDA—an enhanced, open-access database of renewable energy resources in Spain. This database provides wind and solar PV capacity factors (CFs) for the Spanish NUTS3 regions, covering the 1990–2020 period. Special attention is paid to the analysis of the weather patterns associated with the identified events, which are obtained from the ERA5 reanalysis. Finally, this study is part of the WE-Resyst project, which aims to design a renewable energy power system for Spain that is resilient to weather and climate variability and change.

The results showed, firstly, that the proposed event identification method provides more events outside the winter season compared to other reference methods. Secondly, solar PV events showed a mean and maximum duration of 1.2 and 4 days, respectively, compared to 1.4 and 7 days for wind energy. Distinctive weather patterns were identified behind these events. Furthermore, the results showed that: 1) compound solar PV and wind events occur at specific dates, mostly unrelated to the dates of individual solar PV or wind events, and 2) the intensity of compound events, in terms of renewable generation deficit, is lower compared to single-resource events. These results are explained by the existence of a high temporal complementarity between wind and solar resources in the study region during the winter and summer seasons, although with significant interannual variability. As a general conclusion, the characteristics of the solar and wind resources in the study region make the Spanish power system less exposed than others to weather extremes.

How to cite: Pozo-Vazquez, D., Santos-Alamillos, F., Pinilla-Ortiz, L., and Ruiz-Arias, J. A.: Characterizing solar and wind energy droughts in Spain: Identification and weather patterns, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-83, https://doi.org/10.5194/egusphere-plinius19-83, 2026.

Seasonal forecasts represent a promising tool to support water resources management in the Mediterranean region, where water availability is increasingly affected by climate change and the occurrence of extreme events. Knowing in advance the availability of water resources allows for better management of water’s multiple uses, including agriculture and renewable hydropower production.

This study presents an assessment of ECMWF SEAS5 seasonal forecasts (51 members, 0.4° grid spacing, 6h time resolution, seasonally aggregated, with lead times from 1 to 7 months) over Italy, with a focus on their potential applicability for the prediction of water resource availability and, ultimately, hydropower production.

The forecasts cover the period 2018-2024, while a hindcast period 1994-2016 is considered for bias correction purposes and as baseline reference. The forecast performance has been evaluated for 2 m air temperature and precipitation using a high-resolution observational reference dataset from Ispra (IspraObs). This dataset, covering the period 1951-2024 with a spatial resolution of 1km, has been upscaled to 0.4° of resolution, using a conservative remapping algorithm. The performance metrics used include the Anomaly Correlation Coefficient (ACC), correlating forecast and observed anomalies with respect to the climatology of the observational dataset, the RMSE Skill Score (RMSESS), and the Continuous Ranked Probability Skill Score (CRPSS), which compares the cumulative distribution function of forecasts with the one of the reference climatology.

Simple Bias correction approaches, i.e. additive mean adjustment for temperature and multiplicative mean ratio for precipitation, calibrated using hindcast data, have proven to increase the performance of the forecast, particularly for temperature and, to a lesser extent, for precipitation.

Results indicate that temperature forecasts show moderate predictive skill over the country, particularly in summer, with ACC average values above 0.3 at a 4-month lead time, suggesting a reasonable ability to reproduce the observed climatic interannual variability. In contrast, precipitation forecasts show lower and spatially heterogeneous skill, reflecting the intrinsic difficulty of predicting precipitation in the Mediterranean region. In this case, the seasonal forecast skill seems no better than climatology for lead times greater than 1 month, with quite poor performances for lead times greater than 4 months.

 A more specific verification has been conducted over the river basin of Tevere, Central Italy, which is of particular interest for the energy sector in terms of hydropower production. The results show good performances at 3-month lead time in summer: ACC values are in the range 0.6-1, while RMSESS is around 0.4.

Building on these results, future work will focus on integrating the bias-corrected seasonal forecasts into a hydrological modeling chain, to provide estimates of water resource availability for Tevere river basin, at a monthly time scale. This enables the assessment of forecast-driven streamflow predictions and their potential use for optimizing hydropower production in Italy. Such an approach is highly relevant in the context of climate change, as improved seasonal predictability could enhance adaptation strategies for water resource management and energy production in the Mediterranean region.

How to cite: Gambini, E., Sperati, S., Pesce, M., Collino, E., and Gargiulo, A.: Assessing Seasonal Weather Forecasts for Water Resource Management and Hydropower Production, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-32, https://doi.org/10.5194/egusphere-plinius19-32, 2026.

The tourism-oriented Mediterranean Basin is increasingly exposed to intensified thermal stress under ongoing climate change, potentially affecting human health, outdoor activities, and tourism sustainability. Coastal tourism destinations along the eastern Adriatic are particularly vulnerable due to their climatic predisposition, which governs the duration of the tourist season and directly impacts the optimization of infrastructure and overall capacity utilization. This study assesses spatiotemporal changes in thermal risk across major tourism destinations along the eastern Adriatic coast using human biometeorological indicators derived from long-term meteorological observations. This study examines long-term thermal comfort conditions and trends in four highly visited eastern Adriatic destinations and evaluates their climatic suitability for both beach and sightseeing tourism.

Human thermal conditions were evaluated using the modified Physiologically Equivalent Temperature (mPET) index, allowing detailed assessment of heat stress intensity under Mediterranean conditions. Trends in the frequency, duration, and persistence of thermal stress categories were examined in the period 1996-2020 across all destinations.

Results show that over the last 25 years, monthly mean mPET values have increased in every month except May, while severe and extreme heat stress (mPET ≥ 35 °C) has become more frequent, especially in July and August. Although local geography and maritime influences create slight variations between cities, every location shows the same clear trend: summers consistently become uncomfortably hot. This thermal shift increases the touristic attractiveness of the shoulder seasons when comfortable conditions are more frequent. While summer still offers the most favorable climatic conditions for beach tourism, the frequency of beach-comfortable conditions has declined this season. Conversely, thermal conditions for sightseeing have become more favorable in April and November, while deteriorating significantly in September. Surprisingly, a downward trend in May's mPET values indicates that this month is becoming less suitable for the beach but increasingly favorable for sightseeing.

The outcomes suggest increasing vulnerability of East Adriatic coastal tourism systems to climate change, particularly regarding human exposure to prolonged daytime heat stress during the peak tourist season. Our analysis also indicates that, despite the risks of climate change, the tourism sector has a unique 'window of opportunity' to extend the beach season from spring into autumn. Since the shoulder seasons are becoming more comfortable for sightseeing, there is a real chance to adapt by combining the region’s rich cultural heritage with these better weather windows—especially as modern tourists look for more than just a traditional beach holiday.

How to cite: Malinović-Milićević, S., Micić, J., Denda, S., and Pecelj, M.: Adapting Adriatic Tourism to Climate Change: Challenges of Summer Heat and Opportunities for Seasonal Extension, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-16, https://doi.org/10.5194/egusphere-plinius19-16, 2026.

In recent years, the intensification of extreme weather events and increasing exposure to climate risks have made it increasingly clear that organisations need to develop adequate adaptive capacities. The consequences of such events affect not only natural ecosystems, but also operational continuity, resource management, supply chains, and the economic and social sustainability of organisations. In this context, the ability to anticipate, understand and manage the impacts arising from environmental changes represents a strategic priority for public, private and third-sector organisations. Despite the growing attention devoted to the issue, empirical evidence on the factors that foster the development of adaptive capacities and pathways to resilience at the organisational level remains limited (Berkhout et al., 2006).

This study analyses the main determinants of organisational adaptation, focusing on the role of climate awareness and risk perception (Todaro et al., 2021), pressure from stakeholders (Buysse & Verbeke, 2003), and the integration of environmental issues into decision-making and strategic planning processes (Judge & Douglas, 1998). The analysis is based on data collected via a survey of organisations operating across different economic sectors, institutional settings and geographical areas, including private firms, public bodies and third sector organisations.

Preliminary results suggest that a greater perception of the risks associated with climate change is linked to a higher uptake of adaptation practices. Stakeholder pressure also emerges as a key driver for implementing strategies aimed at managing vulnerabilities and reducing exposure to environmental risks. These strategies include risk assessment and monitoring, the use of information and tools to support decision-making, investment in the development of internal skills, and the integration of environmental considerations into organisational processes (Berkhout et al., 2006). The evidence also suggests that organisations characterised by greater adaptive capacity, a stronger focus on environmental issues, greater investment in training and skills development, and higher levels of innovation and organisational learning tend to develop higher levels of resilience, strengthening their ability to respond to the disruptions and uncertainties generated by climate risks (Ambulkar et al., 2015; Gibson & Birkinshaw, 2004).

The study contributes to the scientific debate on climate adaptation by highlighting the role of cognitive, organisational and institutional factors in building adaptive capacity. The findings also provide useful guidance for managers and public decision-makers interested in promoting adaptation pathways, strengthening organisational resilience and supporting the transition towards more sustainable development models capable of addressing the challenges posed by climate uncertainty.

Keywords: climate adaptation; organizational resilience; adaptive capacity; stakeholder pressure; climate risk management.

How to cite: Lombardi, S., Giuttari, E., and Martellozzo, F.: Addressing Climate Change: An Analysis of Organizational Adaptation Practices, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-88, https://doi.org/10.5194/egusphere-plinius19-88, 2026.

Natural or man-made hypogea (such as tombs, catacombs and crypts) are underground environments with a stable microclimate (temperatures rarely above 20°C and a consistently high relative humidity, often close to water vapour saturation). These features result from the combined effect of the high heat capacity of the structure and limited air exchange between the indoors and outdoors. Despite the stable microclimate conditions, the monitoring in such environments requires careful consideration of instrument choice and deployment due to prolonged near-saturation conditions. The THESAN project has been funded by Sapienza University of Rome to investigate the impact of a changing microclimate and microbial dynamics on the preservation of tombs in the Etruscan necropolis of Tarquinia, a UNESCO World Heritage Site in the Mediterranean basin. This contribution describes the microclimate investigation undertaken in selected tombs, where an environmental monitoring has been implemented by the authors since 2024 and it is still ongoing. Particular attention was paid to selecting a sensor to measure relative humidity, which is challenging in such environments. Additionally, the contribution investigates the potential impact of a changing climate on related indoor microclimate conditions. Heat and moisture transfer functions were applied to indoor and outdoor microclimate observations collected in 2024-2026 in order to model indoor temperature and specific humidity based on past and future outdoor conditions. In this way, the evolution of the indoor microclimate from 1940 to 2100 under the Shared Socioeconomic Pathway (SSP) 2-4.5 scenario was analysed. Both microclimate variables increase slowly but steadily in line with the outdoor variables, with their intensity differing only according to the depth of the structures. This is a significant factor when assessing the risk to the preservation of these unique sites, as most degradation, including the spread of microorganisms colonising mural paintings, is induced by microclimate conditions. The investigation enabled the evaluation of the impact of outdoor climate and informs possible future pathways for the management of these sites in a constructive dialogue with microclimatologists, microbiologists, restorers, and the site manager.

How to cite: Frasca, F., Boccacci, G., Chimenti, C., Tomassetti, M. C., Rinaldi, T., and Siani, A. M.: THESAN Project: the role of a changing climate in Mediterranean cultural hypogea, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-40, https://doi.org/10.5194/egusphere-plinius19-40, 2026.

Over recent decades, managers and curators of cultural heritage sites have faced unprecedented challenges in safeguarding cultural and natural heritage (CNH). Archaeological sites, historic parks and gardens, monumental complexes, historic buildings and related collections, cultural landscapes and natural reserves are increasingly vulnerable to the adverse impact of both slow-onset and extreme climate events, alongside anthropogenic pressure. This contribution presents two innovative tools developed within the Interreg Central Europe Project INACO (https://www.interreg-central.eu/projects/inaco/): (i) a “Risk Mapping Tool for Cultural Heritage Protection” to allow accessing and exploiting climate-related indicators, and (ii)CNH-Care, a specialised application designed for assessing the vulnerability of CNH sites exposed to climate extremes. Both tools are web-based and adopt a user-driven, multidisciplinary approach that fosters collaboration among  the scientific community, public authorities, and the private sector. These tools provide knowledge and solutions to support policy and decision makers, curators and cultural heritage managers in the identification of hazard-prone areas and the evaluation of the vulnerabilities at the local scale. The INACO tools enable assessing the risk of cultural heritage assets based on:

• identification of climate and pollution parameters with priority in causing impacts on cultural heritage;
• computing extreme changes in precipitation and temperature using climate extreme indices;
• hazard analysis by exploiting Copernicus satellite services CAMS (Atmosphere Monitoring) and C3S (Climate Change), and other Earth Observation-based data and products;
• development of projections of hazard at territorial level by using outputs from Global/Regional Climate Models from the Euro-CORDEX experiment in the near (2021-2050) and far (2071-2100) future, under two different IPCC scenarios, stabilising (RCP4.5) and pessimistic (RCP8.5);
• vulnerability assessment of cultural and natural heritage with the evaluation of  the physical and socio-economic dimensions of vulnerability;

The INACO tools have been tested in selected European case studies for different types of cultural and natural heritage assets and in three different environmental contexts linked to European river basin districts: sea/river shore, lake shore, and inland river shore. The testing results confirm the feasibility and effectiveness of these tools in optimising preparedness strategies and mitigating climate-related risk.  The ultimate goal is to empower stakeholders and policymakers to integrate dedicated heritage protection measures into national disaster risk reduction and climate adaptation plans,  while fostering the active participation of local communities.

References:

Bonazza, A., and A. Sardella. 2023. Climate change and cultural heritage: Methods and approaches for damage and risk assessment addressed to a practical application. Heritage 6(4): 3578–3589

Bonazza, A.; Bonora, N.; Ducke, B.; Spizzichino, D.; Recchia, A.P.; Taramelli, A. Copernicus in support of monitoring, protection and management of cultural and natural heritage. Sustainability 2022, 14, 2501.

Cacciotti, R., Sardella, A.*, Drdácký, M. & Bonazza, A. (2024). A methodology for vulnerability assessment of cultural heritage at risk due to extreme changes in climate. International Journal of Disaster Risk Science 2024.

Cacciotti, R.; Kaiser, A.; Sardella, A.; De Nuntiis, P.; Drdácký, M.; Hanus, Ch.; Bonazza, A. (2021). Climate change-induced disasters and cultural heritage: Optimizing management strategies in Central Europe. Climate Risk Management, vol. 32, 2021: 1-13

How to cite: Sardella, A., Cacciotti, R., Natali, S., and Bonazza, A.: Sharing experiences in the sustainable management of cultural and natural heritage at risk under climate change scenario: the INACO Project, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-51, https://doi.org/10.5194/egusphere-plinius19-51, 2026.

The Vesuvius National Park (Campania, southern Italy) represents an ecologically and culturally significant protected landscape in the central Mediterranean, encompassing Natura 2000 sites and priority habitats designated under the EU Habitats and Birds Directives. These ecologically valuable areas are increasingly exposed to the growing frequency and severity of wildfire events driven by climate change. Recent fire seasons, including the catastrophic events of 2017 and the large-scale fires of August 2025, have caused extensive damage to forest ecosystems within the protected perimeter, confirming a pattern documented at national level by ISPRA: a substantial proportion of the forest areas affected by fires in Italy falls within the Natura 2000 network.

This contribution presents a multi-temporal remote sensing approach aimed at mapping wildfire impact and monitoring post-fire vegetation recovery within the ecologically sensitive zones of the Vesuvius National Park. The Normalised Burn Ratio (NBR), derived from Sentinel-2 multispectral imagery (Copernicus), is computed for two reference periods using an automated PyQGIS workflow. The differencing of pre- and post-fire NBR values (dNBR) enables the spatial classification of burn severity and the identification of habitat units showing incomplete ecological recovery.

Furthermore, a composite Wildfire Risk Index (WRI) is derived by integrating dNBR-based burn severity with topographic, climatic, and habitat variables as input features to an Artificial Neural Network (ANN) classifier trained on historical fire occurrence data, producing a spatially explicit fire susceptibility map. This methodology, well established in the Mediterranean wildfire literature, allows the identification of high-susceptibility zones within ecologically sensitive habitats, supporting conservation planning and post-fire restoration prioritisation.

The entire workflow relies on an Open Science framework and freely accessible Copernicus Earth Observation data, making it scalable and transferable to other ecologically valuable protected areas across the Mediterranean basin. Results are intended to inform habitat management under the Habitats Directive and to contribute to early-warning and preparedness protocols consistent with the Sendai Framework for Disaster Risk Reduction

How to cite: De Simone, C. S., Giugliano, P., Longobardi, A., and Ronza, M.: Multi-temporal NBR Analysis and Neural Network-Based Wildfire Risk Assessment for Ecologically Sensitive Protected Areas: The Case of Vesuvius National Park, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-86, https://doi.org/10.5194/egusphere-plinius19-86, 2026.

The Mediterranean Basin is typically classified as a region with decreasing streamflow and as a hotspot for future climate change, with important impacts on agricultural and ecosystem functioning. Here we present an assessment of past trends and future projections of water resources at the scale of the Mediterranean Basin. We evaluated how historical climate change, vegetation greening, and reservoir construction affected Mediterranean discharge trends, based on over a century of discharge trends (1914–2022) obtained from 654 discharge stations across the Mediterranean Basin. The results show that mean discharge trends align mostly with precipitation trends between 1921-2000, distinguishing periods of significant increasing (1941–1971) and decreasing discharge (1961–2000). However, between 1981 and 2020 the relationship between precipitation and mean discharge mostly diminishes. We show through multiple linear regression that precipitation and vegetation greenness have an equally strong but counteracting effect on runoff. Reservoir construction caused a reduction of the mean and maximum discharge. Furthermore, we assessed  the impact of climate change on water resources, which is predominantly studied through the application of hydrological models forced by climate model output. Through a systematic review we analysed the results of 262 Mediterranean climate change assessments. We show that runoff is projected to decrease on average with 19%, with a stronger decrease  towards the end of the century and with increasing emission scenarios (up to −39%). Similarly, soil moisture (−14%) and aquifer recharge (−21%) are also negatively affected by climate change, while irrigation demand is projected to increase (8%). While past trends were shown to be heavily affected by vegetation development and reservoir construction, most future hydrological assessments focus solely on the impact of climate change, neglecting vegetation development. This urges future studies to incorporate vegetation development and anthropogenic activities into these assessments, to obtain more accurate water resources projections, including possible feedbacks.

How to cite: Eekhout, J., Boutaghane, H., Dakhlaoui, H., El Khalki, E. M., Uysal, G., Vicente Serrano, S., Nunes, J., Tramblay, Y., and de Vente, J.: Past trends and future projections in water resources in the Mediterranean Basin, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-74, https://doi.org/10.5194/egusphere-plinius19-74, 2026.

The Mediterranean region is considered one of the world’s primary climate change hotspots, where rising temperatures and declining precipitation are expected to intensify droughts and water scarcity. In Albania, the Seman River Basin is of major importance for irrigated agriculture, hydropower production, and regional water supply. This study investigates future hydrological changes in agricultural sub catchments of the Seman Basin using the WASA-SED hydrological model forced with EURO-CORDEX regional climate projections.

Eight EURO-CORDEX regional climate model simulations were evaluated against observed precipitation and temperature data for the period 1991–2020 using a multi-criteria ranking framework. The best-performing climate model combinations were selected, bias-corrected, and applied to six hydrological subcatchments characterized by contrasting elevations and land-use conditions under RCP4.5 and RCP8.5 scenarios for the period 2021–2100.

Results indicate a robust decline in mean annual discharge across all sub catchments during the near future (2021–2050), with projected reductions ranging from 9% to 32% relative to the historical baseline. The most significant and consistent signal is the intensification of summer low-flow conditions, particularly in low-elevation agricultural catchments where irrigation demand is already increasing. High-elevation sub catchments show altered snowmelt dynamics and seasonal runoff redistribution. Long-term projections reveal divergence between emission scenarios: under RCP8.5, increased winter precipitation partially offsets annual runoff reductions in some sub catchments, while summer discharge remains substantially reduced in all scenarios.

The findings highlight the growing vulnerability of Mediterranean agricultural basins to climate-driven hydrological change and emphasize the need for adaptive water management strategies, including irrigation modernization, drought preparedness, and improved reservoir management. This research provides one of the first sub catchment-scale climate-hydrological assessments for Albania and demonstrates the applicability of the WASA-SED model for climate impact studies in data-sparse Mediterranean environments.

How to cite: Doko, A., Kirby, O., and Bronstert, A.: Climate Change Impacts on Water Availability in Mediterranean Balkan River Basins: A Case Study of the Seman River Basin, Albania, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-38, https://doi.org/10.5194/egusphere-plinius19-38, 2026.

How to cite: Dalle Vaglie, M. and Martellozzo, F.: Mapping Decadal Soil Dynamics and Projecting Climate-Driven Degradation Impacts on Global Agricultural Yields: The HUMERIS Framework, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-55, https://doi.org/10.5194/egusphere-plinius19-55, 2026.

Climate change is progressively reducing winter chill accumulation in temperate regions, posing a critical threat to the sustainability of stone fruit production systems. In Mediterranean and semi-arid areas, substantial declines in chill portions are projected in warming scenarios, particularly in traditionally productive zones, compromising the complete fulfillment of chilling requirements (CR) and thus affecting flowering phenology, fruit set, and yield stability. This challenge requires rapid adaptive strategies capable of maintaining crop productivity under increasingly mild winters. In this context, spontaneous somatic mutants (“bud sports”) may represent a valuable yet underexploited genetic resource for climate adaptation. These naturally occurring variants can exhibit altered phenological traits without the need for long-lasting breeding programs. A representative example is ‘Búlida Precoz’, an apricot mutant derived from the widely cultivated ‘Búlida’. ‘Búlida Precoz’ shows a significant reduction in chilling requirements (33.7 vs. 47.5 chill portions, a 29% reduction) and advances flowering by approximately 17 days as compared to ‘Búlida’. From an agroclimatic perspective, the incorporation of such new low-chill alleles into breeding programs has the potential to significantly expand the spatial and temporal suitability of fruit production. Climate projections for Spain indicate that areas currently marginal for high-chill cultivars may remain viable only for genotypes with reduced CR, particularly under pessimistic, high-emission, warming scenarios (RCP8.5), where chill accumulation declines sharply across Mediterranean environments. Here, we apply this agroclimatic framework to the 'Búlida' / 'Búlida Precoz' pair, mapping where the low-chill mutant would still satisfy its CR while the parental cultivar would not. Thus, the deployment of low-chill mutants could enable the maintenance, or even extension, of cultivation areas by aligning genotype requirements with future climatic conditions.

This work highlights the synergistic value of integrating genomics and agroclimatic modeling to address climate-driven constraints in temperate fruit crops. Specifically, it illustrates how the identification and utilization of novel alleles derived from bud-sport mutants can provide an efficient pathway for rapid adaptation to low-chill winters. Finally, these findings support the development of climate-resilient ideotypes and contribute to safeguarding the productivity and economic viability of fruit agroecosystems under current climate change.

How to cite: Campoy, J. A., Egea, J. A., Ruiz, D., and González-Palazón, D.: Leveraging bud sport–derived low-chill alleles to sustain Mediterranean stone fruit production under warming winters, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-105, https://doi.org/10.5194/egusphere-plinius19-105, 2026.

General models predict an increased risk of extinction for various Mediterranean species, particularly those with fragmented populations or restricted distributions. Large-scale models offer an overview of the species that could be affected by climate change, but local or regional scale models are needed. These allow for higher spatial resolutions and the inclusion of local factors, which can significantly influence the actual effects of climate change, especially on populations located near the edges of a species' distribution.

For Testudo graeca, we present the results at different spatial scales (Mediterranean and Southeastern Spain) and using different levels of information. In southeastern Spain, GLM methods were applied to develop presence/absence and abundance models, which were then used to project distribution and abundance under high-resolution (10 km cell) climate scenarios.

The results highlight the need for local-regional models and suggest that more detailed information (abundance) could better represent species' responses during the transition to the future climate, particularly for long-lived species like T. graeca. Overall, the results point to a loss of potential habitat and abundance in the current area of ​​Southeastern Spain, posing a significant challenge for the conservation of a species with limited expansion capacity, like T. graeca.

The research has also revealed divergent results depending on the quality of information that is used. High quality information (high spatial resolution, inclusion of local factors, high quality species information as abundance) is basic to get robust and reliable results to identify priority areas for mid-term monitoring, assessment of extreme events impacts and active conservation measures for the species. High quality information is, therefore, essential for the management and conservation of species under climate change.

How to cite: Martínez-Fernández, J. and Esteve-Selma, M. A.: Challenges for the conservation of Mediterranean vulnerable species under climate change. The case of Testudo graeca, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-69, https://doi.org/10.5194/egusphere-plinius19-69, 2026.

Climate change is expected to alter resource availability, vegetation dynamics, and environmental conditions across Mediterranean ecosystems, with potentially important consequences for agriculture, and particularly for extensive livestock systems. Understanding how environmental conditions influence livestock movement in their occupied ecosystems is therefore essential for predicting the responses of grazing systems to increasing climatic variability and extreme events. We investigated the effects of climate and productivity, land use, and topography on the spatial behaviour of extensive cattle and sheep, at two temporal scales, across the Iberian Peninsula, one of Europe’s most climate-vulnerable Mediterranean regions. We collected GPS data between 2018 and 2024 (total of 16,474,709 locations) from 263 cattle and 702 sheep herds distributed across different climatic conditions (Arid, Temperate and Cold regions). These herds occupied 45.7% of the peninsular territory (2.7x10⁵ km²), distributed throughout 40 Spanish and 3 Portuguese provinces/districts. We estimated annual home range size and daily travelled distance of tracked herds. Generalized linear mixed models and variation partitioning analyses were used to identify the main environmental drivers of livestock movement. Our results indicate that environmental drivers differed markedly between temporal scales. At the annual scale, climate and grassland productivity emerged as the dominant drivers of home range size, explaining the largest unique fraction of variation in both cattle (31.8%) and sheep (24.0%). Home ranges generally decreased as rainfall increases and more productive conditions, indicating that greater resource availability reduces the need for extensive movements. These results suggest that future shifts in precipitation regimes, drought frequency, and vegetation productivity may substantially modify livestock space use. Land-use effects were comparatively weaker, although managed pastures consistently reduced home range requirements. At the daily scale, topography was the main determinant of movement distances, explaining the largest proportion of variation in both cattle (16.1%) and sheep (9.8%). Nevertheless, climatic variables also showed significant non-linear effects, with precipitation and temperature influencing daily displacements in both livestock species. Accumulated rainfall during the previous month was negatively associated with daily movement distances, highlighting the importance of short-term environmental conditions and forage availability. Artificial land cover increased daily movement, whereas agricultural areas generally reduced it. Our findings reveal that extensive livestock movement is highly sensitive to climatic and productivity gradients, particularly at broader spatial scales. In Mediterranean regions, where climate change is expected to intensify droughts and alter vegetation phenology, these responses may reshape grazing patterns, resource use, and ecosystem functioning. By linking large-scale livestock tracking data with environmental drivers, this study provides new evidence of how climate change may affect both agricultural systems and the ecological processes mediated by domestic herbivores, supporting the development of adaptive management strategies for Mediterranean landscapes.

How to cite: Pascual Rico, R., Fernández Gómez, L., Pérez García, J. M., Anadón, J. D., de la Cruz Amo, L., Navez Alegre, L., Acevedo, P., Sánchez Zapata, J. A., and M. Barbosa, J.: Extensive livestock farming movement under climate change, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-110, https://doi.org/10.5194/egusphere-plinius19-110, 2026.

We used the ERA5-HEAT reanalysis to analyze changes in the Universal Thermal Climate Index (UTCI) over Europe from 1940 to 2023, separate the contributions of its meteorological drivers, and map heat vulnerability at NUTS-2 level. The Mediterranean is the region where the signal is clearest: it has warmed quickly, and the bioclimatic and health consequences are now measurable over decades. Across the continent, cold-stress hours decrese fastest in the north (more than 4 h decade^-1), while heat-stress hours increase across southern Europe (more than 3 h decade^-1). In the Mediterranean, the annual heat-stress total already exceeds 670 h, roughly four weeks per year, and is increasing by  4–6 h yr^-1. A one-at-a-time perturbation between 1940–1960 and 2003–2023 attributes most of the rise to 2 m air temperature and mean radiant temperature. At the city scale we analyze 118 cities from 42 European countries. Athens, Seville and Antalya already see 750–1,000 heat-stress hours per year, with trends of 3–4 h yr^-1. A Heat Vulnerability Index was developed that combines heat stress exposure with the population aged 65 and over, population share at risk of poverty, the share of outdoor workers, and GDP per capita as a proxy for adaptive capacity. The index showed values above 0.5 across southern Spain, southern Italy, Greece, Bulgaria and Romania, and above 0.6 in several NUTS-2 regions. The regions where heat exposure is rising fastest are also the regions with the low adaptive capacity, which makes Mediterranean heat a socio-economic problem as well as a meteorological one. That points to two complementary policy directions: urban cooling and green infrastructure on the climate side, and occupational heat-safety rules and heat-health warnings on the public-health side, with older and lower-income residents as the priority group.

How to cite: Antonescu, B., Mărmuranu, L., Ene, D., Andrei, S., and Turcu, R.: Heat stress in the Mediterranean, 1940–2023: trends, drivers and vulnerability, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-35, https://doi.org/10.5194/egusphere-plinius19-35, 2026.

Extreme heat and urban heat island effects increasingly influence outdoor thermal conditions in urban areas during the summer season. Children represent one of the most vulnerable population groups due to frequent outdoor exposure during educational, recreational, and sports activities in schoolyards.

The aim of this study is to investigate micrometeorological conditions and heat exposure in schoolyards within the Belgrade urban area during the warm part of the year. Preliminary measurements are being conducted in two primary schoolyards located in different urban environments. Measurements include sun-exposed and shaded locations, as well as different surface types within each schoolyard, in order to investigate spatial variability of thermal conditions and heat exposure across different micro-locations.

The selected schools were analyzed according to the Local Climate Zones (LCZ) framework, enabling comparison of thermal conditions across different urban morphologies. The research focuses on the influence of vegetation cover, shading conditions, and surface characteristics on heat exposure and outdoor thermal conditions. Particular attention is given to the identification of potentially vulnerable micro-locations within schoolyards.

The results are expected to contribute a better understanding of urban heat exposure in school environments and support future climate adaptation strategies in urban areas.

Key words: urban heat stress, schoolyards, micrometeorological measurements, LCZ, urban bioclimatology

How to cite: Pecelj, M. and Malinovic-Milicevic, S.: Assessment of Heat Stress in Schoolyards in Belgrade (Serbia) Using Micrometeorological Measurements, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-43, https://doi.org/10.5194/egusphere-plinius19-43, 2026.

The relation between atmospheric parameters and glycaemic patterns is a topic of clinical relevance, which needs to be deeply analysed in order to understand the feedback of patients to different environmental condition and therapy. In this context, the results of the project "Innovation Ecosystem: innovation, digitalisation and sustainability for the widespread economy in central Italy (VITALITY)", funded by NextGenerationEU, made it possible to assess how glycaemic trends in diabetic patients respond to external temperatures, humidity and Humidex. In this study analyses performed on both almost 200,000 patients with type 2 diabetes, followed at the Lanciano-Vasto-Chieti (Abruzzo, Italy) Local Health Authority, and on 219 patients with type 1 diabetes followed at the UOSD Regional Paediatric Diabetes Service Hospital, ‘SS. Annunziata’ Hospital, are included. The effect of climate change on diabetic patients was evaluated through correlation studies and multivariate analyses. Atmospheric temperature, humidity and Humidex were assessed with respect to blood glucose patterns both on the entire sample of patients (approximately 200,000 subjects), over 5 years (2019-2023), and on precision basis, following a subset of approximately 50 patients with type 2 diabetes, intensively for one week during 2025. At the same time, the analysis over a period of one year (Autumn 2022 - Summer 2023) on 219 patients with type 1 diabetes, was carried out evaluating glycaemic trends and outdoor temperatures [1,2]. The results point out a strong correlation between environmental conditions and blood glucose levels at every stage of the analysis, highlighting the importance of taking such parameters into account when studying chronic diseases such as diabetes.

[1] Mascitelli, A.; Tumini, S.; Chiacchiaretta, P.; Aruffo, E.; Sacrini, L.; Saltarelli, M.A.; Di Carlo, P. Effect of Atmospheric Temperature Variations on Glycemic Patterns of Patients with Type 1 Diabetes: Analysis as a Function of Different Therapeutic Treatments. Int. J. Environ. Res. Public Health 2025, 22, 1850. https://doi.org/10.3390/ijerph22121850

[2] Chiacchiaretta, P.; Tumini, S.; Mascitelli, A.; Sacrini, L.; Saltarelli, M.A.; Carabotta, M.; Osmelli, J.; Di Carlo, P.; Aruffo, E. The Impact of Atmospheric Temperature Variations on Glycaemic Patterns in Children and Young Adults with Type 1 Diabetes. Climate 2024, 12, 121. https://doi.org/10.3390/cli12080121

How to cite: Mascitelli, A., Chiacchiaretta, P., Staropoli, M. C., Aruffo, E., Tumini, S., Ferretti, A., Franciotti, R., Zhang, N., and Di Carlo, P.: The VITALITY Project: an analysis of the impact of climate change on diabetic patients in a region of central Italy (Abruzzo, Italy), 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-19, https://doi.org/10.5194/egusphere-plinius19-19, 2026.

The Mediterranean basin is one of the regions of the world most exposed to the joint pressure of rising temperatures and persistent tropospheric ozone (O₃) and fine particulate (PM2.5) air pollution. Heatwaves (HW), atmospheric stagnation (STG) and their compound occurrence (CE) are known to influence both pollutant accumulation and human vulnerability. However, the share of the population health burden that can be attributed specifically to each type of day, and to their compound occurrence, has not yet been quantified in a consistent way across the basin.

A high-resolution, end-to-end attribution framework for tropospheric (O₃) and PM₂.₅ mortality is presented under mutually exclusive daily event categories (no-event, HW-only, STG-only and CE) over the Mediterranean basin for the period 2013-2025. Air-quality fields are taken from the CAMS European reanalysis; meteorology from ERA5. HW are defined as maximum temperature exceeding the day-of-year 90^th percentile climatology for at least four consecutive days, and STG follows the Wang and Angell (1999) wind and precipitation thresholds. Concentration-response functions include a log-linear model, two non-linear alternatives (saturating and supralinear-log) and the Global Exposure Mortality Model (GEMM,) for PM2.5. Population fields are derived from the GHSL GHS-POP R2023A product and merged with Eurostat NUTS-3 demographics. Baseline mortality rates combine Eurostat NUTS-3 records with UN World Population Prospects 2024 single-age data, so that countries outside the European Union are also covered.

Over the wide Mediterranean (around 125 million inhabitants), O₃ concentrations on CE days reach 102 µg m^-3 (+38 % above no-event days), with annual O₃-attributable premature deaths  estimated at 2,500 (95 % CI 660–3,630) on CE days, versus 900 (95 % CI 240–1,320) on HW-only days and 820 (95 % CI 180–1,260) on STG-only days. The Relative Excess Risk due to Interaction (RERI), which quantifies whether the joint health effect of heatwaves and stagnation exceeds the sum of their individual effects on an additive risk scale, and the Non-Linear Response Effect (NLRE; Gao et al., 2020), which measures whether pollutant concentrations during CE depart from a linear addition of the HW-only and STG-only responses, displayed heterogeneous spatial patterns. Nonetheless, a localised super-additive behaviour was found over densely populated zones, with positive interaction values over 39% of grid cells in the Mediterranean region, implying that these local hotspots suffer strongly enhanced CE impacts. Alternative temporal definitions of CE further showed that the estimated burden is sensitive to how synchrony between HW and STG is defined: allowing STG to occur within ±1 or ±3 days of a HW increased CE day counts by factors of 1.22 and 1.32, respectively, and raised O₃-attributable mortality from 2,500 deaths yr⁻¹ under the same-day definition to 3,200 and 3,440 deaths yr⁻¹. These results provide a quantitative and reproducible baseline for compound heat-pollution risk in the Mediterranean, and support the design of integrated heat and air-quality early-warning systems for the region.

How to cite: Jimenez-Guerrero, P., Espinosa, N., Gil-Guirado, S., Jerez, S., Montávez, J. P., and Turco, M.: Compound heatwave-stagnation episodes amplify tropospheric ozone and fine particulate matter attributable mortality across the Mediterranean, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-98, https://doi.org/10.5194/egusphere-plinius19-98, 2026.

Numerous studies have demonstrated the impacts of extreme meteorological events and air pollution on public health. Nonetheless, only a few consider the synergy of both factors (compound events) when analysing mortality rates from an atmospheric perspective. This work aims to establish connections between mortality excesses in mainland Spain during wintertime, extreme atmospheric events, and the circulation patterns involved in these episodes. For that, daily mortality rate data at a provincial level are used for the 2015-2022 period.

Winter mortality extremes were categorised and associated with preceding circulation types (CTs), based on sea-level pressure (SLP), temperature at 850 mb, and geopotential height at 500 mb. This classification uses daily average fields derived from ERA5 reanalysis over a domain covering the entire Iberian Peninsula. This classification uses daily average fields derived from ERA5 reanalysis over a domain covering the entire Iberian Peninsula. For each resulting CT, mean fields of temperature, NO2, and PM10 were computed using CAMS reanalysis data. The results show that most mortality extremes succeed extreme atmospheric conditions, with a time lag that depends on the location and variable considered. The variables that better explain mortality include maximum and minimum temperature, nitrogen dioxide (NO2), particulate matter (PM10), and their combinations. Their influences from previous days are significant for more than half of the cases, especially when the compound event comprising extreme minimum temperature followed by high levels of NO2 occurs, with a median lag of about one week.

Regarding the circulation patterns, the results show that most cases of high mortality are linked to anticyclonic systems and warm temperatures at high levels, which can lead to very cold conditions at the ground level and contribute to air stagnation. The situation is exacerbated with the concatenation of CTs related to cold conditions. Extreme mortality occurs when CTs associated with high NO2 levels join persistent low temperatures. This phenomenon may impact multiple provinces simultaneously or within a short timeframe, suggesting that early warning systems should consider these events to alert vulnerable populations and prevent nationwide high mortality rates.

How to cite: Garnés-Morales, G., Jiménez-Guerrero, P., Gil-Guirado, S., García-Fernández, E., Raluy-López, E., Segado-Moreno, L. C., and Montávez, J. P.: Circulation Patterns of Compound Atmospheric Events Associated with Wintertime Mortality Excess in Mainland Spain, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-94, https://doi.org/10.5194/egusphere-plinius19-94, 2026.

While overall the global warming with the causes and global processes connected to well-mixed CO2, and its impacts on global to continental scales are well understood with a high level of confidence, there are knowledge gaps concerning the impact of many other non-CO2 radiative forcers leading to low confidence in the conclusions. This relates mainly to specific anthropogenic and natural precursor emissions of short-lived GHGs and aerosols and their precursors. These gaps and uncertainties also exist in their subsequent effects on atmospheric chemistry and climate, through direct emissions dependent on changes in e.g., agriculture production and technologies based on scenarios for future development as well as feedbacks of global warming on emissions, e.g., permafrost thaw. 

The main goal of EC HE project FOCI, is to assess impacts of key radiative forcers and the processes of their impact on the climate system, to find and test an efficient implementation of these processes into global ESMs and into RCMs coupled with CTMs, and finally to use the tools developed to investigate mitigation and/or adaptation policies incorporated in selected scenarios of future development targeted at Europe and other regions of the world. We are developing new regionally tuned scenarios based on improved emissions to assess the effects of non-CO2 forcers. 

Overall introduction to coupled RCM-CTM modelling experiment strategies and evaluation simulations will be presented in addition to the contemporary status of the project. Historical simulations results are validated against reanalyses data and the assessment of impact of chemistry involvement is shown. We will show the results for regional and local conditions in high resolution for City of Prague. Future scenario (SSP3-7.0) is running for full and low NTCF to provide the comparison and effects of these non-CO2 forcers in future, while in historical validation full chemistry simulation is compared to run without chemistry.

Acknowledgement: Project FOCI (Non-CO2 Forcers and Their Climate, Weather, Air Quality and Health Impacts), has been co-funded by the European Union with funding from the European Union’s Horizon Europe Research and Innovation Action under grant agreement No. 101056783 and from UKRI under the UK Government’s Horizon Europe Guarantee (UKRI Reference Numbers: 10040465, 10053814 and 10050799).

How to cite: Halenka, T., Sokhi, R., Finardi, S., and Machado-Crespo, N.:  Chemistry – Climate Interactions over Scales: Project FOCI - Non-CO2 Forcers and Their Climate, Weather, Air Quality and Health Impacts , 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-130, https://doi.org/10.5194/egusphere-plinius19-130, 2026.

Urban areas modify the exchanges of energy, moisture, and momentum between the surface and the atmosphere through the combined effects of materials, urban morphology, and anthropogenic emissions. These modifications influence both local meteorological conditions and air quality, generating a complex system of interactions. While urban climate affects the transport, dispersion, and accumulation of atmospheric pollutants, air pollution can also alter radiative processes and influence local meteorology, leading to a coupled atmosphere–chemistry system.

This study investigates the interactions between urban climate and air quality over the metropolitan areas of Madrid and Murcia (Spain) using the WRF-Chem model. A set of high-resolution simulations was performed employing a one-way nested configuration, with an outer domain covering the Iberian Peninsula and two inner domains centered on the target cities. Pollutant emissions were represented using a high-resolution downscaled inventory that resolves major emission sources, including road networks, industrial areas, airports, and agricultural land uses. Four main experiment families were considered: rural and urban configurations, each with and without atmospheric chemistry. Additional sensitivity experiments were conducted to assess the impact of emission strength and urban representation.

The experimental framework allows assessment of both the influence of urban processes on pollutant distributions and the impact of atmospheric composition on urban meteorology. Particular attention is paid to the role of urban canopy models in shaping near-surface thermal patterns and local circulations, as well as to the extent to which urban-induced meteorological modifications affect air-quality conditions across the metropolitan area.
The results highlight the interactions between urban climate and atmospheric chemistry and emphasize the importance of realistically representing urban morphology and emissions in coupled modeling systems.

Acknowledgments: The authors acknowledge the ARUBA project (PID2023-149080OB-I00/MCIN/AEI/10.13039/501100011033, Ministerio de Ciencia e Innovación/Agencia Estatal de Investigación, Spain & FEDER, EU), and the INSIEME project (FSRM/10.13039/100007801). ERL thanks her predoctoral contract FPU (FPU21/02464) to the Ministerio de Universidades of Spain.

How to cite: Raluy-López, E., Segado-Moreno, L., Cordero, A., and Montávez, J. P.: Urban climate and air quality feedbacks: a high-resolution WRF-Chem study, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-72, https://doi.org/10.5194/egusphere-plinius19-72, 2026.

Cities play fundamental role in climate at local to regional scales through modification of heat and moisture fluxes, as well as affecting local atmospheric chemistry and composition, alongside air-pollution dispersion. Vice versa, regional climate change impacts urban areas and will affect cities and citizens increasingly in the next decades when the population in urban areas is growing projected to reach 70 % by 2050. This is critical in connection to extreme events, e.g. heat waves with extremely high temperatures exacerbated by the urban heat island effect, in particular during night-time, with significant consequences for human health.

Recent RCM development achieved resolution of city scales within convection permitting RCMs, parameterization of urban processes thus becomes more important. From the framework of CORDEX FPS, main aims and progress of FPS URB-RCC will be presented, from the results based on previous available simulations to the results of analysis of Stage-0 experiments using case studies of heat wave, within ensemble of about 40 simulations for Paris with CP RCMs. This experiment shows the effects of different implementation of urban parameterizations as well as of the different models and their settings on urban heat island under the heat wave. Further outlook of long term (10 years – Stage 1 experiment) climate simulation with these models in common strategy of IMPETUS4CHANGE Horizon Europe Project will be presented. The development of Global Satellite Cities experiment with similar experiments for other big cities around the world will be introduced as another part of Stage 1 experiment. Clear emphasis is given to urban heat island, with possibility to compare the signal for different types of megacities.

Acknowledgement: Project I4C (Impetus4Change), has been funded by the European Union with funding from the European Union’s Horizon Europe Research and Innovation Action under grant agreement No. 101081555.

How to cite: Halenka, T., Langendijk, G., Hoffmann, P., Belda, M., and Machado-Crespo, N.:  CORDEX Flagship Pilot Study URB-RCC: Urban Environments and Regional Climate Change, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-132, https://doi.org/10.5194/egusphere-plinius19-132, 2026.

Microplastics (MPs) have emerged as an atmospheric contaminant of growing concern due to their widespread presence, long-range transport potential, and possible impacts on human health and ecosystems. While numerous studies have investigated airborne MPs in urban and remote environments, the contribution of wildfires to atmospheric MP emissions remains largely unexplored. Vegetation, soils, litter, and anthropogenic materials accumulated in forested areas can contain substantial amounts of plastic particles, which may be released into the atmosphere during combustion processes.

This work presents a preliminary assessment of the atmospheric transport and distribution of wildfire-derived microplastics over Portugal using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). A novel emission database for MPs released by biomass burning was developed based on available literature, emission factor estimates, wildfire inventories, and assumptions regarding the plastic content of combustible fuels. MPs were represented as inert particulate matter and incorporated into the modelling framework as a passive tracer to investigate their transport pathways and atmospheric fate.

The model was applied to selected wildfire episodes in Portugal, with particular emphasis on large fire events characterised by intense smoke emissions and regional-scale atmospheric transport. Simulations were used to quantify the spatial and temporal evolution of airborne MPs concentrations, identify source-receptor relationships, and evaluate the potential for long-range transport beyond the affected regions.

The results indicate that wildfire emissions can generate detectable MP plumes extending hundreds of kilometres from the source areas under favourable meteorological conditions. Elevated concentrations were found not only in the vicinity of the fires but also in downwind urban and rural regions, highlighting the role of atmospheric transport in redistributing MPs across large spatial scales.

The study demonstrates the feasibility of incorporating MPs into chemistry transport models, and provides a first step towards understanding the contribution of extreme events to atmospheric MP concentrations. Future work will focus on refining emission estimates, improving the representation of MP physicochemical properties and deposition processes, and evaluating simulations against field measurements collected within the framework of the PlasURE project. These developments will contribute to a more comprehensive assessment of the environmental and health implications of airborne MPs under present and future climate conditions.

Acknowledgments: This work was supported by: (i) national funds through FCT/MECI: LEPABE, UID/00511/2025 (https://doi.org/10.54499/UID/00511/2025) and UID/PRR/00511/2025 (https://doi.org/10.54499/UID/PRR/00511/2025) and ALiCE, LA/P/0045/2020 (https://doi.org/10.54499/LA/P/0045/2020); (ii) COMPETE 2030, Portugal 2030, and the European Union, within project PlasURE - Impact of airborne microplastics: urban and rural environments and extreme events, with number 16721 and operation code at the Funds Platform COMPETE2030-FEDER-00790200; (III) the ARUBA project (PID2023-149080OB-I00/MCIN/AEI/10.13039/501100011033, Ministerio de Ciencia e Innovación/Agencia Estatal de Investigación, Spain & FEDER, EU); (IV) and project INSIEME (FSRM/10.13039/100007801).

How to cite: Segado-Moreno, L., Ratola, N., Jiménez-Guerrero, P., and Montávez, J. P.: Wildfires as an emerging source of microplastics: transport and regional impacts over Portugal, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-71, https://doi.org/10.5194/egusphere-plinius19-71, 2026.

This work has received the support by POSAHPI-2 (PID2022-143146OB-I00), SNOWDUST (TED2021-130114B-I00) and PYRENEES4CLIMA (LIFE-2022-STRAT 101104957). Thanks to AEMET for their support and facilities. 

How to cite: Pey, J., Bandrés, J., López-Moreno, J. I., and Valero-Garcés, B. L.: Long-Range Aerosol Transport to the Central Pyrenees: Impacts of Wildfire Smoke, Saharan Dust and Climate-Driven Events, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-50, https://doi.org/10.5194/egusphere-plinius19-50, 2026.

Wildfire behaviour is becoming increasingly volatile, expressed through more frequent and pronounced episodes of anomalously intense fire activity. Conventional approaches to characterising wildfire intensity, particularly those based on satellite-derived fire radiative power, remain strongly tied to fire occurrence, making it difficult to distinguish between periods of widespread burning and genuinely anomalous or extreme fire behaviour.

Here, we demonstrate that departures from expected relationships between fire detections and energy release reveal increasingly frequent and pronounced episodes of anomalous fire behaviour. These anomalies are characterised not only by elevated total energy release, but by shifts in the upper tail of the fire energy distribution, indicating a growing prevalence of disproportionately intense fire activity. Importantly, this behaviour does not occur uniformly, but instead reflects distinct modes of fire activity, ranging from widespread high-energy burning to more localised, extreme events.

Across multiple regions and scales, these patterns point to a broader increase in wildfire volatility, defined by growing variability and instability in fire energy behaviour over time. This suggests that fire regimes are not only intensifying but becoming less predictable and more prone to rapid departures from expected conditions. Within this framework, Mediterranean ecosystems emerge as exhibiting episodic volatility, characterised by punctuated extreme fire activity, underscoring their sensitivity to climate-driven risk.

This emerging volatility has important implications for wildfire management under a changing climate. As fire behaviour becomes increasingly unstable, existing assumptions around fire growth, intensity, and spread may become less reliable, complicating forecasting, planning, and response. Recognising and accounting for increasing volatility will be critical for adapting wildfire management strategies to a future in which extreme and anomalous fire behaviour plays a more dominant role.

How to cite: Derler, Z., Little, K., Flannigan, M., Belcher, C., and Kettridge, N.: Fire regimes are becoming increasingly volatile: implications for managing extreme fire events in the Mediterranean, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-12, https://doi.org/10.5194/egusphere-plinius19-12, 2026.

Background: Wildfires in Southern Europe arise from interacting climatic, ecological, and socio-ecological mechanisms.
Drought enhances fuel desiccation, land cover change reshapes vegetation flammability, and the expansion
of the wildland–urban interface (WUI) increases ignition pressure and exposure. Understanding how these drivers
overlap spatially and temporally is essential to identify where reinforcing or decoupled processes shape wildfire
dynamics. This study develops a spatially explicit framework integrating drought variability (Standardized Precipitation–
Evapotranspiration Index, SPEI), Landscape Flammability Classes (LFC), and Wildland–Urban Interface (WUI)
expansion to detect statistically supported hotspots and coldspots of wildfire occurrence across biogeographical
regions.
Methods: We analysed a 20-year dataset (2001–2020) at 12-km resolution, combining number of fire and fire size
with long-term trends in three macro-drivers (SPEI, LFC, WUI). Temporal changes in wildfire parameters were estimated
using generalized linear models with False Discovery Rate (FDR) correction. Trends in SPEI and WUI were
assessed through Mann–Kendall and Kendall tau tests supported by Theil–Sen slope estimation, while LFC change
was derived from land-cover transitions between 2000 and 2018. Finally, a spatial co-occurrence analysis classified
each grid cell as a hotspot, coldspot, or mismatch area based on the degree of alignment between macro-driver
trajectories and wildfire trends.
Results: Significant and candidate hotspots were concentrated in the Anatolian, Continental, and Mediterranean
bioregions, where over 30% of burned areas showed concurrent increases in drought intensity, landscape flammability,
and WUI expansion. The Anatolian bioregion exhibited the strongest increases in WUI (+ 73.4%) and LFC (+ 67.2%),
while the Continental region was dominated by widespread drying (90.5% of its area). Coldspots were mainly located
in the Atlantic region, reflecting coherent declines in both wildfire parameters and macro-drivers. Mismatch zones,
encompassing more than half of the burned area, revealed high spatial variability where fire dynamics diverged
from macro-driver trends, indicating the influence of local-scale or non-mechanistic processes.
Conclusions: The joint analysis of climate variability, fuel continuity and human pressures shows that wildfire patterns
in Southern Europe depend on how the long-term trends of these macro-drivers align or decouple. Hotspots reveal
regions where multiple drivers evolve in the same direction as wildfire activity, whereas mismatch areas highlight
the role of local processes that interrupt large-scale relationships. The framework provides a quantitative basis

How to cite: Cappelluti, O., Ascoli, D., Oliveira, S., Lafortezza, R., Chiriacò, M. V., Sanesi, G., and Elia, M.: Intertwined drivers of wildfire occurrence in Southern Europe: climate, landscape flammability and WUI expansion, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-20, https://doi.org/10.5194/egusphere-plinius19-20, 2026.

Accurate wildfire prediction is becoming increasingly critical as climate change drives warmer and drier conditions worldwide. The complex, non-linear interactions among meteorological factors, fuel characteristics, and landscape structure make wildfire risk a primary candidate for advanced machine learning (ML) approaches that integrate Earth Observation (EO) and climate data. In contrast to traditional operational risk systems commonly based only on weather conditions, these ML-EO systems can be trained on a much richer context, allowing the generation of not only more accurate wildfire occurrence risk maps but also the potential corresponding impacts at a much higher spatial resolution.

To demonstrate this paradigm shift, we present a multi-scale set of modeling developments that address the wildfire lifecycle from onset to impact. We begin at the landscape scale with a 100m calibrated daily probability of occurrence model that combines the Fire Weather Index (FWI), high-resolution land cover data, and historical fire event records. For all subsequent models, we deliberately neglect the highly unpredictable ignition component by focusing exclusively on burned areas to predict potential behavior in the event of a fire. Within this framework, we first explore the estimation of active fire intensity, evaluating how environmental drivers can enable the prediction of potential Fire Radiative Power (FRP). Moving further to evaluate the final physical consequences on the landscape, we introduce a 30m potential wildfire severity model for predicting vegetation damage in ecosystems; just from initial conditions, the model successfully identifies critical thresholds and skillfully predicts which specific areas within a fire's perimeter would be most severely burned. Finally, to capture the key role that spatial context plays in fire behavior, we explore Convolutional Neural Networks (CNNs) aiming to learn fire connectivity patterns directly from historical events and enabling the modelling of valuable variables for fire managers, such as the size of a potential wildfire event. Together, these developments mark a significant step toward an operational, high-resolution and comprehensive wildfire risk pipeline strengthening both early-warning capabilities and long-term resilience planning.

How to cite: Peña-Izquierdo, J., Perpinyà-Vallès, M., Cendagorta-Galarza, D., Florindo, C., Huertas, C., Teruel, D., Folguera, G., Llort, J., and Romero, L.: From Occurrence to Impact: A Multi-Scale Machine Learning Pipeline for High-Resolution Wildfire Modelling, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-106, https://doi.org/10.5194/egusphere-plinius19-106, 2026.

Fire lookout towers remain a critical component of early detection systems in Mediterranean countries. However, the effectiveness of tower networks is constrained by topographic visibility limitations, creating significant surveillance gaps in forested landscapes. This study presents a national-scale GIS-based visibility analysis of Türkiye's 548 forest fire lookout towers and identifies priority surveillance deficit zones by integrating historical fire records, forest stand characteristics, and road network accessibility.

Viewshed analysis was conducted using a 30-metre resolution NASA SRTM digital elevation model under curved-earth parameters, with an observer height of 6 metres and a smoke detection height of 100 metres, consistent with operational standards defined in the General Directorate of Forestry's Communiqué No. 285. The resulting binary visibility surface was overlaid with three datasets: the 12 regional forest directorate boundaries, a national forest stand map comprising 3,998,699 polygons with species composition and structural attributes, and a georeferenced dataset of 30,883 wildfire incidents recorded between 2013 and 2023.

Results indicate that the existing tower network provides visibility coverage over 47.6% of Türkiye's forested territory, leaving 52.4% as blind spots. Regional analysis reveals substantial disparities, ranging from near-complete coverage in the Aegean and Marmara regions (Kütahya 99.2%, Çanakkale 98.5%) to near-zero coverage in northeastern regions (Artvin 0.0%, Erzurum 0.1%). Species-level analysis shows that fire-prone pine species such as Pinus brutia (86.6%) and Pinus nigra (87.8%) are relatively well covered, whereas Picea orientalis (0.2%) and Pinus sylvestris (43.5%) stands fall predominantly within blind spots. Analysis of historical fire records reveals that 75.1% of all recorded fires occurred within visible zones, while 24.9% (n=7,618) originated in areas invisible to any tower.

Optimized Hot Spot Analysis (Getis-Ord Gi*) applied to 5,356 wildfire incidents occurring in forested blind spots identified 251 statistically significant priority surveillance deficit zones. These zones are concentrated predominantly in Şanlıurfa (69 hotspots, 502 fires), Elazığ (46 hotspots, 381 fires), Adana, Trabzon, and Hatay. Road network accessibility analysis using OpenStreetMap data confirmed that 99.2% of identified hotspot zones are accessible via the existing road network, based on a connectivity threshold of 4,000 metres derived from the road-access pattern of the existing tower network.

These findings reveal structural surveillance gaps in Türkiye's fire detection network, particularly in southeastern and eastern Anatolia and the Black Sea region. The study provides a data-driven framework for prioritising surveillance deficit zones and recommends evaluating complementary detection technologies such as unmanned aerial vehicles and automated camera systems for areas where conventional tower infrastructure is insufficient.

How to cite: Küçükosmanoğlu, M. A. and İnan, M.: National-Scale GIS-Based Visibility Analysis of Fire Lookout Towers and Identification of Surveillance Deficit Zones in Türkiye, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-56, https://doi.org/10.5194/egusphere-plinius19-56, 2026.

Catastrophic wildfires are increasing, encroaching further into populated areas. It is extremely important to be prepared when wildfire strikes. By preparing the home and property for wildfire and knowing what to do if evacuation is necessary, the safety and the survivability can be dramatically increased.

Get Ready

Hardening the home: a home can be hardened by retrofitting it with ignition-resistant or noncombustible materials to protect against the threat of flying embers, direct flame contact and radiant heat exposure.

Defensible space: defensible space is the buffer created between a building on the property and the plants, brush, trees, or other combustible items in the near vicinity. This buffer helps to keep wildfire away from the home by reducing the fire’s intensity and slowing or halting the spread of wildfire. Creating this space also provides protection for the firefighters defending the home.

Fire smart landscaping: taking it into consideration can be crucial to reduce the spread of wildfire around the home.

Get set

Create a wildfire action plan: such plan must be prepared and familiar to all members of the household well in advance of a wildfire.

Keep necessary items ready if immediate evacuation required: pets, important papers, prescriptions, PC, plastic cards, etc.

Prepare an emergency supply kit: put together an Emergency Supply Kit/Go Bag before a wildfire occurs and keep it easily accessible to take when evacuation occurs.

Be prepared for power outages: power outages may occur before and during the threat of a wildfire. It’s important to be prepared and know what actions to take when leaving the home during a power outage.

Have a family communication plan: have one in place in case family members get separated.

Insurance preparedness: maintain insurance, know what your policy covers, make home inventory before evacuating.

Go!

Prepare pre-evacuation steps: when evacuation is anticipated and if time allows check one more time outside the house, inside the house, animals.

Implement evacuation steps: review the evacuation checklist. Take the Emergency Supply Kit. Cover up to protect against heat and flying embers. Locate and take pets.

Know when to evacuate: leave when evacuation is recommended by fire officials to avoid being caught in fire, smoke or road congestion. In an intense wildfire, emergency personnel may not have time to knock on every door. If danger is imminent, the best course of action is to evacuate. If advised to leave, don’t hesitate!

Anticipate about animal evacuation: after family and home safety, don’t forget about pets and livestock. Their chances of surviving a wildfire can be increased with some advanced planning.

Know what to do if trapped: while in vehicle, while on foot, while in the home.

Returning home after a wildfire: always check with officials before attempting returning home after a wildfire. Be aware of dangers that exist after a wildfire.

How to cite: Katay, Z.: Wildfire preparedness, awareness and action plan - ready, set, go !, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-2, https://doi.org/10.5194/egusphere-plinius19-2, 2026.

Under climate change and shifting fire regimes, a wildfire can trigger forest responses ranging from full recovery to shifts toward non-forest states. Understanding the trajectories of forests after fire and the effectiveness of post-fire management and restoration strategies is essential for designing sustainable forest management. However, our capacity to learn from local field studies is limited as they lack the capacity to extrapolate results to broader scales, and scientific syntheses often suffer from non-standardised data generation. Such limitations can be tacked by conducting coordinated, distributed studies, in which many sampling sites are collaboratively implemented following a common protocol across large geographic regions. This approach allows responding research questions broadly as well as robustly assessing the drivers of heterogeneity.

The FireTran project aims to establish an international distributed research network across Mediterranean countries to monitor post-fire forest trajectories and experimentally test the effect of small-scale restoration treatments in modulating these trajectories. The project aims to collaboratively monitor dozens of sites across the region –under small local effort– to quantify regeneration dynamics and assess the drivers of heterogeneity at plot, site, and regional scales. Additionally, voluntary experimental treatments (tree planting, seeding, soil transfer) can be implemented at a subset of participating sites. Remote sensing will help locate field plots and, through integration with field data, it will allow to assess large-scale drivers through spatial upscaling.

The FireTran project will soon initiate a local pilot phase in Granada. The study protocol will build on the lessons learned therein and learn from consultation with scientists and stakeholders. It will be published to invite scientists from Mediterranean countries to participate in the distributed study by establishing local sites. The protocol will establish the scientific aims, network structure and governance, field methods, requirements for co-authorship, and the data management approach. The presentation will provide a general overview of the project, invite the audience to provide input for the protocol, and screen their prospective willingness to participate by establishing local field sites.

How to cite: Leverkus, A. B. and Beierkuhnlein, C.: A new Mediterranean network to assess post-fire forest trajectories: Invitation for input and participation, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-117, https://doi.org/10.5194/egusphere-plinius19-117, 2026.