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 90th 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 (Tx) 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 Tx in the reference period 1981-2010, computed over summer days only. Formally, the threshold is given by us = Q0.95 (Tx,t,l t ∈ [1981, 2010], l ∈ [1, 92]) where Tx,t,l denotes the daily maximum temperature at station s on day l of year t. An EHE is then defined through the indicator Ix,t,l = 1 if Tx,t,l > us , 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.
The territory of Ukraine is highly vulnerable to dry phenomena due to its temperate continental location, extensive agricultural lands, and increasing climate variability. Of particular concern are rapidly developing droughts or flash droughts and intense dry-hot winds, both capable of causing severe crop damage.
The occurrence and evolution of flash droughts during the warm season (April–October) of 1980–2024 were analysed using the Standardized Evapotranspiration Deficit Index (SEDI) based on actual and potential evaporation data from the GLEAM project. Flash droughts were identified using SEDI at the 4-week time scale, while daily-scale SEDI values were applied for analysis with dry-hot wind events. Dry-hot winds (known in Ukraine as “sukhovey”) were identified from observation records at 34 stations using threshold criteria of air temperature, relative humidity, and wind speed adopted by the National Hydrometeorological Service of Ukraine.
The highest number of flash drought episodes (up to 30–35 events) was recorded in western and northern Ukraine. Positive trends in drought occurrence prevailed across most regions, especially in the southwest, centre, and north, whereas negative trends were found in the west and parts of eastern Ukraine. Flash droughts in western regions were generally short-lived (2–3 weeks), while the longest events (6–8 weeks) occurred in southwestern and central Ukraine. Most flash drought episodes were highly intense, frequently reaching extreme drought conditions (SEDI < −2.0), although their intensity showed a general decreasing trend during the study period.
Five major flash drought episodes affecting at least 20% of Ukraine were identified during 1980–2024, lasting from 3 to 7 weeks. In most cases, dry-hot winds developed after drought onset, with their frequency increasing toward the middle of drought episode. Under dry conditions, dry-hot winds were associated with increased SEDI values, indicating temporary weakening of drought intensity. Thus, dry-hot winds do not initiate flash droughts but may influence their spatial development through changes in intensity.
How to cite: Semenova, I. and Vicente-Serrano, S. M.: The relationship between flash drought and dry-hot winds in Ukraine, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-15, https://doi.org/10.5194/egusphere-plinius19-15, 2026.
The Mediterranean basin is a highly vulnerable climate change hotspot where severe summer heatwaves are predominantly driven by persistent atmospheric blocking (e.g., Omega blocks) over the Euro-Atlantic sector. While Dynamical Seasonal Forecast Systems (SFS) are crucial for early warning, they frequently exhibit biases in maintaining these low-frequency blocking ridges, casting doubt on whether their temperature forecasts are dynamically consistent or merely the result of thermodynamic tuning.
In this study, we introduce a novel, physics-informed 3D Convolutional Neural Network (CNN) to evaluate the dynamic-thermodynamic coupling in SFS models. Unlike standard AI architectures, our model utilizes a Sequential "Macro-to-Micro" spatial funnel (scaling from 19x19 to 7x7 spatial kernels) combined with a Convolutional Block Attention Module (CBAM). This architecture forces the network to first isolate the planetary-scale stationary wave before analyzing embedded synoptic transient eddies, mimicking the causal fluid dynamics of blocking maintenance.
Trained using a self-adapting focal loss on normalized anomalies of ERA5 reanalysis data, the deep ensemble creates a highly robust, bias-free "AI Blocking Index." We apply this ERA5-trained ensemble directly to the seasonal hindcast anomalies of selected C3S models [ECMWF SEAS5 and CMCC]. By cross-referencing the AI-detected blocks within the SFS troposphere against the SFS lower-tropospheric thermodynamic forecasts (specifically the 850hPa-layer Temperature fields over the Mediterranean basin), we bypass surface-level boundary noise to quantify the pure internal consistency of the dynamical models. Ultimately, this framework is designed to highlight potential divergences between SFS air-mass temperatures and physical circulation, serving as an independent diagnostic tool to identify model drift and bias-correct seasonal extremes.
Acknowledgements: This research was supported by the PREVENT project that has received funding from the EU Horizon Europe framework programme (grant no. 101081276)
How to cite: Manios, E. M., Velikou, K., Papadopoulos Zachos, A., Tolika, K., and Anagnostopoulou, C.: Evaluating Dynamic-Thermodynamic Coupling in Seasonal Forecasts: Linking Atmosphere Blocking to Mediterranean Heatwaves via Deep Learning, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-26, https://doi.org/10.5194/egusphere-plinius19-26, 2026.
The Mediterranean region is widely recognized as a climate change hotspot, where the increasing frequency and intensity of extreme phenomena pose significant threats to both environmental stability and socio-economic resilience. Rising temperatures, shifting precipitation patterns, and prolonged droughts have led to heightened risks of heatwaves, flash floods, and agricultural stress across the basin. Identifying the underlying atmospheric drivers of these events is critical for improving early warning systems and developing effective adaptation strategies. However, traditionally applied correlation methods fail to provide robust evidence regarding the physical causality behind the analyzed connections.
Using the Peter and Clark momentary conditional independence (PCMCI) causal discovery approach, the current study examines the causal relationships between temperature (including mean temperature, and its minimum and maximum values), precipitation, and soil moisture in the studied region. This advanced approach allows for the quantification of robust causal links while accounting for multivariate dependencies and time lags. To account for regional climatic heterogeneity, the Mediterranean is partitioned into eight subregions using k-means clustering based on temperature and soil moisture profiles. The study evaluates the causal influence of large-scale teleconnection patterns and Synoptic Weather Types (WTs), during both summer and winter seasons.
Results indicate a strong influence of Western patterns during winter, particularly the North Atlantic Oscillation (NAO). Furthermore, the analysis reveals an important influence from eastern drivers during the summer months, notably through the Indian Summer Monsoon and the Madden-Julian Oscillation (MJO). By quantifying the strength of these causal links and identifying the specific weather types that lead to adverse conditions, this research offers a more rigorous understanding of synoptic mechanisms than traditional correlation-based methods. These findings are crucial for enhancing seasonal forecasting and advancing climate resilience in the Mediterranean Basin.
Acknowledgements: This research was supported by the PREVENT project that has received funding from the EU Horizon Europe framework programme (grant no. 101081276)
How to cite: Papadopoulos Zachos, A., Velikou, K., Manios, E. M., Di Capua, G., and Anagnostopoulou, C.: Causal Drivers of Mediterranean Temperature and Drought: A Time-Lagged Network Analysis using PCMCI and Synoptic Weather Types, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-29, https://doi.org/10.5194/egusphere-plinius19-29, 2026.
Significant droughts occurred during the 19th century in the Iberian Peninsula causing severe social and economic consequences. Such events are typically studied through quantitative indices like the Standardized Precipitation Index (SPI); however, in this case study, instrumental rainfall data only reliably cover the last thirty years of the century. The limited spatial coverage of these early instrumental data justifies the use of historical documentary sources for the study of droughts during this transitional century between the purely pre-instrumental period and the modern instrumental era. In this work, we developed drought indices based on rogation ceremonies from municipal documentary sources compiled in the AMARNA® Platform (Multidisciplinary Archives for Analysis of Natural and Anthropogenic Risk) and analyzed two atmospheric indicators from the 20CRv3 reanalysis: sea-level pressure and geopotential height at 500 hPa.
The results show a decrease in the sensitivity of historical drought records starting in the mid-19th century, likely due to social and political changes. Additionally, although historical data on drought impacts are mainly documented during late winter and spring, critical seasons for harvests, the atmospheric configurations likely conducive to droughts occurred predominantly during the winter prior to the social response. The complexities of historical data, such as the delays between the onset of a meteorological drought and the documentation of its impacts, combined with the inherent physical propagation of water deficits through natural systems, underscore the necessity of considering time lags when studying historical climate phenomena.
The nineteenth century presents distinct difficulties for drought reconstruction. This is not only because of the decline in civil administrative sources recording drought rogation ceremonies but also because it corresponds to the early stage of institutional meteorological records, which are characterized by a limited number of observation points and still-developing methodologies. Despite these challenges, the availability of reanalysis data opens new avenues for the study of a period highly relevant period for understanding drought behavior from a historical perspective. At the same time, the historical data used in AMARNA do not encompass all the documentary sources available in Spain. Fortunately, Spain’s documentary heritage offers considerable potential for further research through both supra-municipal and ecclesiastical administrative records.
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: Ragon, E., Barriendos, J., Barriendos, M., and Pino, D.: Reconstructing Historical Droughts in Spain (1806–1865): Atmospheric Dynamics versus Qualitative Impact Records, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-60, https://doi.org/10.5194/egusphere-plinius19-60, 2026.
At the end of October 2024, a cut-off low (DANA in Spanish) became completely displaced from the basic westerly current. Its interaction with local topography, combined with a strong inflow of moisture from the Mediterranean Sea, triggered one of the most intense weather events in recent Spanish history. Between October 28 and November 4, exceptionally heavy and persistent rainfall was recorded across several provinces. The most severe day was October 29, when multiple national rainfall records were broken at the Turís weather station, including a total of 581 l/m2 in just four hours.
The aim of this study is to reconstruct the episode using both observational data and numerical simulations, with special focus on October 29. We defined the study area over the Segura Basin and the Valencian Community. We analysed the main meteorological structures that developed during the day, their evolution, and how they were reflected in different key weather variables. Finally, the study focuses on the Turís supercell, which produced the most extreme rainfall and is considered the most significant convective structure of the entire episode.
How to cite: Jara Lopez, E. and Montávez Gómez, J. P.: Analysis and numerical simulation of the Exceptional Rainfall Event over the Iberian Peninsula between October 28 and November 4, 2024, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-78, https://doi.org/10.5194/egusphere-plinius19-78, 2026.
It is observed that extreme weather events, particularly short-duration high-precipitation events, have been intensifying in recent years over the Mediterranean and Black Sea regions under the influence of warmer sea surface temperature. On 10–13 August 2021 over the northeastern Black Sea region, an extreme precipitation event occurred in association with a low-pressure system where the sea surface temperature anomalies were 3°C higher.
In order to improve our understanding of how such late-summer low-pressure systems may evolve under future climate conditions, we applied the Pseudo-Global Warming (PGW) method using the Weather Research and Forecasting model at convection-permitting resolution. Counterfactual future scenarios were generated by defining climate-change-deltas which is future periods (2025-2049, 2050-2074, 2075-2099) minus historical period (1990-2014). These climate-change-deltas derived from CMIP6 models under SSP2–4.5, SSP3–7.0, and SSP5–8.5 scenarios were added to ERA5 initial and boundary conditions.
The simulations indicate that future warming can substantially intensify the dynamical structure of the event. While the control simulation which is driven by ERA5 represents the system as a relatively weak low-pressure disturbance, the future PGW experiments produce a much deeper and more organized cyclone. In several simulations, the system develops tropical-like characteristics over the Black Sea which we call blackcane, with a warm-core structure, enhanced low-level convergence, and stronger vertical motion. Cyclone phase-space analysis confirms this structural transition, indicating that future warming promotes the development of a more symmetric warm-core cyclone with stronger blackcane characteristics. These dynamical changes are accompanied by a remarkable increase in near-surface wind speed. In the control simulation, maximum wind speed remains below severe-cyclone intensity, reaching 89 km/h. In the future-climate simulations, maximum wind speeds increase dramatically, reaching 132–181 km/h in the strongest forcing experiments. Minimum sea-level pressure also decreases to below 975 hPa, reaching about 969–970 hPa.
These findings suggest that warmer sea surface temperature and future atmospheric warming may not only enhance extreme precipitation but also support the development of deeper, stronger, and more hazardous blackcane cyclone.
The numerical calculations reported in this thesis were partially performed using high-performance computing resources provided by TÜBİTAK ULAKBİM High Performance and Grid Computing Center (TRUBA) and Sigma2, the National Infrastructure for High-Performance Computing and Data Storage in Norway.
How to cite: Sahinoglu, S., Onol, B., and Gokturk, O. M.: Intensification of Tropical-Like Cyclones Over the Black Sea In the Future Climate: Blackcane Simulations, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-84, https://doi.org/10.5194/egusphere-plinius19-84, 2026.
In March 2026, storm Jolina developed over the central Mediterranean, producing severe weather conditions across southern Italy before moving on to Libya. During its evolution, the system transitioned from an extratropical cyclone toward a tropical-like structure, generating intense winds and heavy precipitation, particularly over Calabria.
In this work, Jolina is investigated through a set of numerical simulations performed with the WRF model to explore the sensitivity of storm evolution and precipitation patterns to different configurations and sea surface temperature (SST) conditions. Simulations are initialized and forced using ERA5 reanalysis, while high-resolution SST datasets from Copernicus are adopted to represent present-day Mediterranean thermal conditions alongside idealized warmer / cooler SST perturbation scenarios.
The analysis focuses on both the cyclone structure and the associated rainfall impacts over southern Italy. Storm evolution is examined using standard dynamical and thermodynamical diagnostics. Simulated precipitation fields, with a focus on southern Italy, are evaluated against satellite- and gauge-based observations.
The experiments are designed to assess how simulation strategies and SST conditions may modulate air–sea interaction, convective organization, and precipitation processes during the evolution of storm Jolina. Preliminary analyses suggest that SST perturbations may influence the spatial organization and local intensity of precipitation over southern Italy, while their role in modulating the overall storm evolution remains under investigation.
How to cite: Fanelli, C., Miglietta, M. M., and Avolio, E.: The Mediterranean Storm ‘Jolina’: Sensitivity to SST and Model configuration on Heavy Rainfall and Tropical-Like Development, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-104, https://doi.org/10.5194/egusphere-plinius19-104, 2026.
Global warming alters the hydrological cycle, increasing heavy rainfall events worldwide. In October 2024, Valencia (Spain) experienced rainfall accumulations in a few hours surpassing annual averages (771.8 mm in 16 h in the official weather station at Turís) and breaking the record for one hour rainfall accumulation in Spain (184.6 mm), resulting in 230 fatalities. Here, we present a physical-based attribution study employing a km-scale pseudo-global warming storyline approach to assess the contribution of anthropogenic climate change. We show that present-day conditions led to a 20% °C⁻¹ increase in 1-hour rainfall intensity, exceeding Clausius-Clapeyron scaling. This intensification was driven by enhanced atmospheric moisture from warmer sea surface temperatures, leading to increased convective available potential energy, stronger updrafts, and microphysical changes including elevated graupel concentrations. These results demonstrate that anthropogenic climate change could intensify the occurrence of flash-floods in the Western Mediterranean region: in this particular case, it intensified the 6-h rainfall rate by 21%, amplified the area with total rainfall above 180 mm by 55%, and increased the volume of total rain within the Jucar River catchment by 19% compared to the pre-industrial era. This study highlights the urgent need for effective adaptation strategies and improved urban planning to reduce the growing risks of hydrometeorological extremes in a rapidly warming world.
How to cite: Calvo-Sancho, C., Díaz-Fernández, J., González-Alemán, J. J., Halifa-Marín, A., Miglietta, M. M., Azorin-Molina, C., Prein, A. F., Montoro-Mendoza, A., Bolgiani, P., Morata, A., and Martín, M. L.: Human-induced climate change amplification on storm dynamics in Valencia’s 2024 catastrophic flash flood, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-108, https://doi.org/10.5194/egusphere-plinius19-108, 2026.
Every time that deep convection develops, the Mediterranean region faces the possible impacts of downburst-induced wind extremes that originate within, and the sub-km scale of these events is below the resolution of operative numerical weather prediction models. However, pre-convective environments often provide an opportunity to assess the possibility of thunderstorms developing downbursts, and recent studies have shown that machine learning provides skillful approaches to derive severe weather probabilities from these environments. However, pre-convective environments often provide an opportunity to assess the possibility of thunderstorms developing downbursts, and recent studies have shown that machine learning provides skillful approaches to derive severe weather probabilities from pre-convective environments.
In this study, we employ a machine learning model to derive the probability of downburst occurrence, derived from convective parameters characterizing pre-convective environments. The model has been trained and tested on 10 years of downbursts and non-severe thunderstorms over Spain that have been identified using lightning records, public reports of severe weather and automated weather stations; with the ERA5 reanalysis providing a representation of the atmospheric structure associated with these events.
Several training procedures have been explored in order to achieve model robustness and avoid biases arising from the underrepresentation of public-source reports in rural areas. Regarding sample generation, these include spatially uniform subsamples of non-severe thunderstorms, oversampling of the minority class of downbursts or restrictions to common-points in downbursts and non-severe thunderstorms. To reduce noise and overfitting risk arising from the large number of candidate convective parameters, a forward selection retains only parameters that improve model performance. The hyperparameters of the model and resampling methods are tuned by a cross-validation based on permutating left-apart years. Finally, the model is tested on new data covering 2 years, measuring its performance with metrics and diagrams adequate for rare phenomena such as False Alarm Rates (FAR), the Critical Success Index (CSI), the Performance-Diagram and its Area Under the Curve (AUPDC) or the attributes diagram.
The most skillful configuration of the model performs better than any individual convective parameter, in terms of performance metrics. Explainability methods and convective parameter selection are coherent with the physical knowledge of downburst winds, highlighting the role of a warm unstable lower-troposphere favoring downdrafts, as well as strong mid-level winds that can be transported downward. Probability estimations improve those of a random model based on the observed climatological frequency of downburst in thunderstorms, although probability outputs close to 1 show elevated uncertainty, as indicated by bootstrap confidence intervals. Another aspect to improve concerns the elevated number of false alarms, a consequence of class imbalance (estimated in 3 downbursts per 100 thunderstorms).
The applications of this model include the coupling with km-scale models, which cannot directly resolve sub-km downbursts but can provide high-resolution depictions of the pre-convective environments that the model takes as input.
How to cite: Barrio-Martin, A., Calvo-Sancho, C., Plaza-Martín, N. P., Azorin-Molina, C., Prein, A. F., Vicente-Serrano, S. M., Gimeno, L., Nieto, R., Chen, D., McVicar, T. R., Zeng, Z., and Morata, A.: Diagnosing Downburst-prone environments with machine learning, 19th Plinius Conference on Mediterranean Risks, Murcia, Spain, 6–9 Oct 2026, Plinius19-109, https://doi.org/10.5194/egusphere-plinius19-109, 2026.
