This session aims at promoting a multi-disciplinary approach to identify and prepare shared solutions and practices, to safeguard both natural systems and human livelihoods in one of the world’s most climate-sensitive regions. Studies of observed past changes and/or future climate projections focused on physical (including extremes, teleconnections, hydrological cycle) and biogeochemical (including biodiversity) aspects of MCRs and other global hotspots are welcome. Similarly, climate change related social aspects, including indigenous knowledge in mitigating climate risks, are well received. Analyses where multiple MCRs are considered and compared are highly appreciated.
As extremes represent one of the primary challenges of present and future climate change over MCRs and other global hotspots, in this session we want also to offer an interdisciplinary platform for researchers applying Extreme Value Theory (EVT) and related approaches to exchange ideas, connect across disciplines, and showcase advances that improve the inference and prediction of extremes, with particular emphasis on environmental and geoscientific applications. We particularly encourage contributions that bridge EVT with climate, hydrology, and infrastructure risk applications, including decision-relevant uncertainty quantification and studies of compound or cascading extremes. Submissions may include new methodological developments, open datasets and tools, or real-world case studies.
Orals: Fri, 8 May, 14:00–15:45 | Room 0.31/32
The broader Mediterranean Basin is a climate hotspot, warming faster than the global average and most other inhabited regions, including areas with similar Mediterranean-type climates. Global and regional projections indicate an acceleration of warming, combined with shifts in the hydrological cycle and more frequent and/or intense extreme events, leading to amplified impacts on societies and ecosystems. Given its distinctive combination of climatic and geographical features, rapid urbanization, high coastal concentration of population and assets, and rich yet diverse socio-cultural contexts, climate change poses a profound and multidimensional challenge to the Mediterranean region. This contribution will synthesize current knowledge on key climate risks, highlight emerging evidence on cascading hazards, and discuss sustainable, nature-based solutions and adaptation pathways specifically tailored to Mediterranean conditions.
How to cite: Zittis, G.: Climate change in the Mediterranean: Emerging risks and sustainable adaptation pathways, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17491, https://doi.org/10.5194/egusphere-egu26-17491, 2026.
How to cite: Bordoni, S., Tootoonchi, R., Battisti, M., D'Agostino, R., Lembo, V., Liguori, G., Ingrosso, R., and Cozzoli, F.: From Noise to Signal: The Future Emergence of Mediterranean Drought, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16640, https://doi.org/10.5194/egusphere-egu26-16640, 2026.
Mediterranean summers are projected to become drier under global warming, with a large inter-model spread. However, models with stronger global-mean warming produce little additional drying. Using Coupled Model Intercomparison Project Phase 6 simulations, we show that this muted sensitivity arises because thermodynamically driven drying is offset by dynamically induced wetting. Changes in vertical motion linked to dynamic response dominate the drying uncertainty, controlled by two independent sea surface temperature patterns: enhanced warming over the subpolar North Atlantic and over the equatorial eastern Pacific for a given level of global warming, with the former intensifying as warming increases. These warming patterns influencing vertical motion are mediated by dry enthalpy advection, whereby subpolar North Atlantic warming exerts a stronger upper-tropospheric temperature-induced effect, while eastern Pacific warming primarily affects the mid-to-lower troposphere through zonal-wind anomalies. These findings clarify why models diverge under identical greenhouse-gas forcing and highlight the central role of warming patterns.
How to cite: Biasutti, M., He, L., and Kushnir, Y.: Future Mediterranean summer drying across models: opposing dynamic and thermodynamic constraints, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3605, https://doi.org/10.5194/egusphere-egu26-3605, 2026.
Heatwave characteristics in Mediterranean climate regions are commonly quantified using percentile-based temperature thresholds, yet the influence of climatological baseline choice on these metrics is often overlooked. Here, we examine how different baseline windows affect heatwave thresholds and how these changes propagate through heatwave statistics across the Mediterranean region. Using ERA5-Land daily maximum and daily mean temperatures, heatwaves are identified under a consistent percentile framework (P95–P99) while varying the baseline period (1981–2010, 1981–2020, 1991–2020).
Rather than focusing on absolute climatological values, we analyze spatially aggregated differences in heatwave count, duration, and magnitude induced solely by baseline selection. The results reveal systematic and climate-dependent sensitivities: warmer baseline windows lead to elevated thresholds, fewer detected events, longer maximum durations, and mixed responses in heatwave magnitude. These effects are not uniform but vary strongly with elevation, land cover, and Köppen–Geiger climate zones. Dry and transitional Mediterranean climates show the largest sensitivity, while forested and high-elevation regions are comparatively less affected. Heatwaves defined using daily maximum temperature exhibit stronger baseline dependence than those based on daily mean temperature.
The findings demonstrate that baseline selection alone can substantially alter heatwave statistics, highlighting the need to explicitly account for threshold sensitivity when comparing heatwave characteristics or assessing climate-related risks in Mediterranean-type regions.
How to cite: Yang, Y., Margarint, M., and Tarolli, P.: Heatwave statistics under changing baselines: threshold sensitivity across Mediterranean climate regimes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10098, https://doi.org/10.5194/egusphere-egu26-10098, 2026.
Understanding how temperature extremes evolve under climate change requires distinguishing between shifts in the typical magnitude of extreme events (location) and changes in their variability (scale). While time-varying scale has been proposed in extreme value analyses, estimating it reliably remains challenging: station-level approaches yield high uncertainty, and changes in scale are easily confounded with location shifts or absorbed by other model components.
We address this through a Bayesian hierarchical framework that pools information across a dense observational network while preserving spatial flexibility. Spatial structure is captured via a Matérn field implemented through the SPDE approach and through covariate effects, while temporal dynamics enter through random walks for location and flexible parametric structures for scale. This hierarchical sharing of information reduces uncertainty in scale estimation compared to single-station analyses. Comparing models with time-constant, linear, and nonlinear scale evolution allows formal testing of whether observed changes arise from location shifts alone. The tail shape parameter was explored but found consistently indistinguishable from zero, indicating that changes are governed by location and scale rather than by increasing tail heaviness.
Application to a century-long record (1916–2024) of annual temperature maxima from a dense observational network reveals a pronounced acceleration in location since the mid-1970s, accompanied by a systematic contraction in scale—a pattern we term "warming with consolidation." This defines a new normal for temperature extremes: summers that once would have been exceptional are now routine, occurring year after year with diminishing contrast between hot years and moderate ones. Meanwhile, reduced spatial variability means that extreme heat increasingly affects entire regions simultaneously rather than isolated areas. Paradoxically, while moderate extremes have become pervasive, the most exceptional events—those with high return periods—grow less steeply than location-only models would predict. The result is a climate where extremes are less surprising but more inescapable.
The framework is transferable to other regions and variables, providing a principled tool for characterising non-stationary extremes and informing climate adaptation.
How to cite: Beguería, S., Vicente-Serrano, S. M., Halifa, A., El-Kenawi, A., Gil-Guallar, M., and Royo-Aranda, A.: Warming with Consolidation: The New Normal of Temperature Extremes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6810, https://doi.org/10.5194/egusphere-egu26-6810, 2026.
Extreme value theory is routinely applied to derive design precipitation values for engineering and risk management. Typically, it is found that precipitation extremes belong to the Fréchet limiting type. Physical arguments, however, suggest they should have stretched-exponential tails, which belong to the domain of attraction of the Gumbel type. We investigate hundreds of sub-daily precipitation records in the Alps for which a classification into convective and non-convective storms is available. At durations of 1 to 6 hours the annual maxima from the heterogeneous samples appear to have heavier tails than the ones of the parent processes. Describing the parent processes using the stretched-exponential tails predicted by physics allows us to explain this apparent tail behavior. Assuming asymptotic convergence on non-convergent heterogeneous processes may lead to a systematic overestimation of the probability of particularly large extremes. Our results challenge the assumptions behind the use of extreme value theory for sub-daily precipitation, with implications for how design precipitation values are determined.
How to cite: Marra, F., Dallan, E., Canale, A., Prosdocimi, I., Papacharalampous, G., Borga, M., and Papalexiou, S. M.: When extreme value theory fails: the case of precipitation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5562, https://doi.org/10.5194/egusphere-egu26-5562, 2026.
Estimates of extreme coastal flooding depend critically on how interacting processes are represented within flood models. For tropical cyclones, storm surge and wave-driven run-up evolve on different time scales and rarely peak simultaneously, yet many statistical and hydrodynamic flood analyses reduce events to static maxima or impose simplified dependence structures. These modeling choices implicitly determine which combinations of processes are treated as plausible extremes, but their influence on inferred flood behavior is rarely examined explicitly.
Here, we investigate how assumptions about temporal structure affect the characterization of compound tropical cyclone flooding by focusing on how alternative representations of storm evolution modify extreme water level estimates and their interpretation. To this end, we employ the Multivariate Spatio-Temporal Maxima with Temporal Exposure (MSTM-TE) framework by Sando et al. (2024) [1] as a diagnostic and generative framework for reconstructing and simulating storm time series under different assumptions about temporal coherence among metocean drivers.
The analysis is based on a 1000-year synthetic tropical cyclone dataset for the Guadeloupe archipelago (French Antilles), which enables direct comparison between modeled extremes and reference behavior across multiple coastal sites with contrasting exposure conditions. To mimic realistic data constraints, only a limited subset of storm events corresponding to a 50-year period is used for statistical calibration, while the remaining events are retained to evaluate the consequences of modeling assumptions for extreme flood characterization. Extreme total water levels are derived from reconstructed storms at multiple coastal sites with differing exposure to tropical cyclones, using analytical wave run-up formulations that allow surge and wave contributions to be examined jointly in time.
Results show that assumptions about temporal structure play a dominant role in determining both the magnitude and variability of estimated extreme water levels. Approaches that neglect temporal coherence tend to promote unrealistically aligned surge–wave combinations, leading to inflated return levels and ambiguous physical interpretation. In contrast, reconstructions that preserve temporal structure yield narrower uncertainty ranges, reduce upward bias in return-level estimates, and reveal distinct site-specific flood-generating mechanisms. At wave-exposed locations, the upper tail of total water levels is associated with short-lived peaks in wave energy, whereas at more sheltered sites, extreme flooding arises from the coincidence of elevated surge with moderate run-up rather than from either component in isolation.
By explicitly linking modeling assumptions to changes in flood extremes, this study highlights temporal structure as a key source of uncertainty in compound flood analysis. The results demonstrate how spatio-temporal reconstruction frameworks can be used not only to estimate extremes, but also to diagnose the physical plausibility of modeled flood scenarios, offering insights that are directly relevant for flood risk assessment in data-limited coastal regions.
[1] Sando, K., Wada, R., Rohmer, J., & Jonathan, P. (2024). Multivariate spatial and spatio-temporal models for extreme tropical cyclone seas. Ocean Engineering, 309, 118365. https://doi.org/10.1016/j.oceaneng.2024.118365
How to cite: Chung, M., Wada, R., Rohmer, J., and Jonathan, P.: Temporally Coherent Modeling of Compound Tropical Cyclone Flooding and Its Role in Extreme Water Level Estimation , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8454, https://doi.org/10.5194/egusphere-egu26-8454, 2026.
The Mediterranean region is undergoing a significant increase in the frequency and severity of atmospheric and marine heatwaves, a trend that has accelerated in recent decades and is projected to continue throughout the 21st century. These extreme heat events pose significant risks to human health and ecosystems, particularly in densely populated coastal urban areas.
Sea breezes, the dominant local summer wind circulation in the region, can mitigate heat stress by transporting cooler and more humid marine air inland during the daytime, potentially reducing coastal temperatures by up to 10 °C depending on urban conditions. However, recent studies have reported instances in which heat is aggravated in urban environments under sea breeze conditions, highlighting the complexity of their interactions with urban heat dynamics. In a warming climate, a weakening trend in sea breeze speeds has been observed at several sites worldwide, including in the Mediterranean region, a climate change hotspot. The reduction may be driven by a warmer Mediterranean, and preliminary results based on observations point to atmospheric heatwaves as the cause, potentially exacerbating heat stress in coastal cities by limiting natural ventilation.
In this study, we analyze nearly 30 atmospheric heatwave episodes from 1981 to 2021 occurring concurrently with sea breezes across the Mediterranean, using the Weather Research and Forecasting (WRF) model, and compare the simulated changes in sea-breeze intensity with meteorological observations to elucidate the dynamic mechanisms behind the observed weakening and to assess whether subsidence induced by overlying subtropical ridges contributes to a hypothesized flattening of the sea breeze circulation. Our preliminary results reveal a consistent reduction in sea-breeze intensity during heatwave conditions across the region, alongside a systematically shallower planetary boundary layer height, indicating a reduced vertical extent of the sea breeze circulation. These findings have important implications for coastal Mediterranean cities, as weaker sea breezes during heatwaves may exacerbate extreme heat, challenge adaptation measures, and increase the vulnerability of urban populations during prolonged warm periods.
How to cite: Bedoya-Valestt, S., Fernandez-Alvarez, J. C., Azorin-Molina, C., Di Napoli, C., Calvo-Sancho, C., Plaza-Martin, N. P., Gimeno, L., Andres-Martin, M., and Chen, D.: Weakened sea breeze circulation driven by atmospheric heatwaves in the western Mediterranean, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1181, https://doi.org/10.5194/egusphere-egu26-1181, 2026.
Understanding the evolving characteristics of extreme precipitation in the Mediterranean Basin is a critical scientific priority amid ongoing climate change. In particular, the observational analysis reveals an apparent paradox in several areas of this region: while total annual precipitation declines, the frequency and magnitude of concentrated heavy rainfall events do not decline, and in some cases even increase. To elucidate the physical mechanisms underlying this seemingly contradictory behavior, we examine the interplay among marine, atmospheric, and topographic factors, and quantify the contribution of rising sea surface temperatures (SSTs) to the amplification of extreme precipitation events.
The methodological framework is based on the numerical reconstruction of twenty precipitation events that occurred during an active wet season extending from September to December 2019. These events are simulated using the Weather Research and Forecasting (WRF) model, configured at a convection-permitting resolution (2 km as horizontal grid spacing). The simulations are initialized and constrained using ERA5 reanalysis data. To isolate and quantify the specific influence of SST evolution on precipitation dynamics, we implement a PGW (Pseudo Global Warning) approach incorporating three distinct SST scenarios: a baseline configuration utilizing observed 2019 SST values, a retrospective scenario employing SST conditions representative of approximately 1980 (-1 °C), and a prospective scenario incorporating SST increases (+3 °C) consistent with end-of-century projections under various Shared Socioeconomic Pathways (SSPs).
The high-resolution WRF simulations demonstrate robust skill in reproducing atmospheric circulation features and the spatial distribution of precipitation across the complex orographic terrain. Comparative analysis across SST scenarios reveals that elevated SSTs increase the frequency of intense precipitation over terrestrial areas, primarily by increasing atmospheric moisture availability. However, the absolute magnitude of peak rainfall accumulations overland exhibits relatively modest sensitivity to SST variations, as the highest precipitation predominantly occurs offshore.
This investigation underscores the added value of convection-permitting atmospheric modeling approaches in capturing the physical processes governing precipitation extremes in topographically complex Mediterranean coastal environments. The findings contribute substantively to reconciling the apparently paradoxical coexistence of declining annual precipitation totals with intensifying daily precipitation extremes, a pattern with profound implications for water resource management, flood risk assessment, and climate adaptation strategies in vulnerable Mediterranean communities.
How to cite: Senatore, A., Furnari, L., Nikravesh, G., Castagna, J., and Mendicino, G.: Contrasting Trends in Daily Precipitation Extremes and Annual Totals over Southern Europe: Modeling the Role of Mediterranean Sea Surface Warming, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14273, https://doi.org/10.5194/egusphere-egu26-14273, 2026.
This work presents an extensive evaluation of long-term variability in dry-spell characteristics across Spain over the period 1961–2024. The analysis combines classical non-parametric approaches with an innovative non-stationary probabilistic methodology applied to exceedance series of dry-spell durations. Daily precipitation records from a dense, quality-controlled observational network were used to identify dry spells according to four precipitation thresholds (0.1, 1, 5, and 10 mm), allowing a detailed characterization of duration distributions. Generalized Pareto Distributions were estimated assuming both stationary and non-stationary formulations. Optimal exceedance thresholds were selected through a systematic percentile-based procedure, and differences between stationary and non-stationary return levels were evaluated using a bootstrap significance test. Additional analyses assessed trends in annual dry-spell frequency, average duration, and maximum dry-spell length.
The results consistently indicate that dry-spell dynamics in Spain are largely stationary. Significant non-stationary behaviour in the GPD location parameter is detected at only a very limited number of stations, while non-stationary representations of the scale, shape, or all parameters combined do not yield meaningful improvements and substantially increase uncertainty. These conclusions are reinforced by conventional trend analyses, which show that the majority of stations (more than 70–85%, depending on the precipitation threshold) display no statistically significant trends in frequency, mean duration, or maximum duration of dry spells. Spatial signals are weak and fragmented, and estimated return levels for rare events (e.g., 50-year return periods) remain remarkably stable throughout 1961–2024. Overall, the findings provide strong evidence for long-term stationarity in the hazard probabilities of extreme dry spells across Spain.
How to cite: Vicente Serrano, S. M., Beguería, S., Royo, A., El Kenawy, A., Franquesa, M., Halifa, A., María, A.-M., Crespillo, A., David, P.-P., Fernando, D.-C., Cesar, A.-M., Gimeno, L., Nieto, R. O., and Gimeno-Sotelo, L.: Non-stationary probabilities of dry-spell hazard in Spain, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3914, https://doi.org/10.5194/egusphere-egu26-3914, 2026.
Posters on site: Fri, 8 May, 10:45–12:30 | Hall X5
Flood events cause billions of dollars in economic losses annually, and these losses are projected to increase as precipitation intensifies and exposure expands. Linking observed flood losses to the statistical rarity of the triggering precipitation is essential for understanding current risk and for distinguishing between large losses triggered by very extreme events and those driven by more moderate events with high exposure.
We present a modular framework that links pluvial and rain-triggered fluvial floods in Europe to the frequency of the precipitation events that caused them. The workflow integrates historical flood event catalogues and high-resolution gridded climate datasets. Each flood event, characterized by date, type, affected region, and reported losses, is assigned a spatial footprint, initially based on administrative units and refined using river basin information where available. Within these footprints, precipitation statistics (e.g. one-hour maximum rainfall) are extracted and converted into return periods. This standardization allows events from different regions and years to be compared on a common frequency scale. The flexible design accommodates various datasets, footprint definitions, and temporal windows, making it suitable for integration with insurance records. By systematically linking pluvial and rain-triggered fluvial flood damages to the frequency of the triggering precipitation events, the framework can support more focused and effective flood risk management strategies.
How to cite: Samantaray, A. and Messori, G.: A Modular Framework Relating European Flood Losses to Rainfall Return Periods, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3650, https://doi.org/10.5194/egusphere-egu26-3650, 2026.
Quantifying the intensity and frequency of extreme precipitation remains a fundamental challenge in climate science, particularly in regions with limited observational records. While Global Climate Models (GCMs) often estimate extremes with bias and Machine Learning (ML) approaches lack interpretability, we investigate whether the complicated spatial variability of extremes can be captured by a low-dimensional climate manifold. We propose a modelling framework based on Extreme-Value Theory (EVT) to assess the annual maximum 1-day (Rx1day) and 5-day (Rx5day) precipitation using three physically interpretable covariates. We construct a non-stationary Generalized Extreme Value (GEV) model where location and scale parameters are driven by the mean and standard deviation of precipitation in the wettest month, and structurally constrained by the Köppen–Geiger climate class. The model is fitted to 85 years of ERA5 reanalysis data, and uncertainty is quantified through bootstrapping. Validation against empirical quantiles demonstrates that this simple, low-order framework can successfully reproduce the spatial patterns and magnitude of local precipitation extremes. These findings suggest that precipitation extremes can be understood in terms of basic hydroclimatic constraints, providing a theoretical baseline for benchmarking complex models and assessing the predictability of extremes in global models, with potential applications in flood management, infrastructure design, and (re)insurance pricing in data-poor locations.
How to cite: Liu, A., Simpson, E., and Brierley, C.: A Climate-Informed Generalized Extreme Value Model for Global Precipitation Extremes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10147, https://doi.org/10.5194/egusphere-egu26-10147, 2026.
Precipitation over the Mediterranean is strongly modulated by large-scale circulation and cloud-regime variability, posing persistent challenges for climate model evaluation. Standard model assessments based on aggregated precipitation metrics often mask regime-dependent errors and limit physical interpretability. Here, we present a Weather-State(WS)-based framework for evaluating Mediterranean precipitation in climate models, combining satellite observations with model simulations in a physically consistent manner.
Daily precipitation from the TRMM dataset (1998-2016) is analyzed together with cloud-regime information derived from ISCCP-based Weather States. The evaluation focuses on historical simulations from CMIP climate models over the Mediterranean (30°–45°N, 10°W–40°E). As a baseline, model-observation differences in total precipitation, precipitation intensity and precipitation frequency are first assessed to identify large-scale discrepancies. WS-conditioned diagnostics are then used as a complementary layer to examine precipitation characteristics within dynamically coherent regimes.
Within this framework, precipitation frequency, intensity, and spatial structure are evaluated conditional on WS occurrence, allowing regime-dependent behavior to be compared across models and observations while reducing the influence of regime mixing inherent in climatological metrics. The analysis further quantifies the contribution of individual WSs to total precipitation and examines the consistency of WS-dependent patterns and trends across models.
The analysis highlights the role of Weather-State-conditioned diagnostics in structuring model evaluation and enabling physically consistent comparison in structuring model evaluation and enabling physical comparison of precipitation characteristics across regimes, supporting improved understanding of model behavior without reliance on fixed assumptions about future change.
How to cite: Konsta, D., Kotroni, V., Lagouvardos, K., and Tselioudis, G.: Weather-State-based evaluation of Mediterranean precipitation in climate models using satellite observations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11019, https://doi.org/10.5194/egusphere-egu26-11019, 2026.
The Mediterranean is widely recognized as a climate-change hotspot, where rapid warming increases evaporative demand and puts pressure on regional water availability. Although many studies have examined long-term precipitation trends, the role of daily evaporation dynamics in shaping aridification remains unclear. Here, we investigate whether extreme evaporation events (ExEvEs) contribute to the region’s accelerating aridification. Using high-resolution precipitation and evapotranspiration datasets for 1980–2023, we analyze annual water availability (P–E), moisture flux ((P + E)/2), and the frequency and intensity of ExEvEs. Our results reveal nearly stationary precipitation but steadily rising evapotranspiration, accompanied by a strong intensification of ExEvEs that accelerates moisture loss and amplifies short-term land–atmosphere feedbacks. These findings suggest that Mediterranean aridification is increasingly driven by evaporative extremes rather than persistent precipitation deficits, with important implications for water-resource planning and climate-adaptation strategies in this highly sensitive region.
How to cite: Rahmati Ziveh, A., Thakur, V., and Markonis, Y.: Aridification is Driven by Water-Cycle Acceleration Over the Mediterranean Region, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-757, https://doi.org/10.5194/egusphere-egu26-757, 2026.
Freezing rain is among the most damaging winter weather hazards, yet robust statistical characterization of its extremes remains challenging due to data sparsity, strong spatial variability, and low signal-to-noise ratio in distribution tails. The traditional Maximum Likelihood Estimation (MLE) approach for estimating Generalized Pareto Distribution (GPD) parameters frequently demonstrates instability when applied to sparse datasets. This often necessitates ad hoc parameter clipping to prevent physically implausible tail behavior. Furthermore, the MLE approach provides limited uncertainty quantification and systematically underestimates risk at higher return periods. This study develops a Bayesian framework for GPD fitting for robust tail risk estimation of freezing rain hazard over North America.
We reconstruct ice accretion for historical event footprints from 43 years of ERA5 reanalysis data (1980–2022) using the Crawford et al. (2021) cyclone tracking algorithm. Freezing rain is identified using ERA5 precipitation type, and ice accretion is computed using the Jones (1998) formulation. Freezing rain occurrences within 1,500 km of tracked extratropical cyclone centers are aggregated into event-level accumulations. After systematic footprint cleaning to remove duplicates and truncated events, several hundred independent freezing rain events are obtained across the domain.
Bayesian GPD fitting is implemented using Markov Chain Monte Carlo (MCMC) sampling with weakly informative priors for the shape and scale parameters. Exceedance thresholds are defined as the 2-year return period level where statistically estimable; in data-sparse regions where the 2-year return period cannot be reliably determined, a minimum accumulation threshold is applied instead. We systematically compare Bayesian and MLE approaches through Event Exceedance Frequency (EEF) curves at multiple locations and return period maps across key economic exposure regions including the Northeast, Southern Plains, and Pacific Northwest, where freezing rain causes significant infrastructure damage.
Analysis indicates that the Bayesian approach yields smoother and more stable tail estimates. Return period maps from the Bayesian framework demonstrate substantially improved agreement with historical observations, with spatial clustering patterns that better capture known climatological gradients and topographic influences. The Bayesian fits demonstrate superior goodness-of-fit, particularly in the extreme tail, where divergence from MLE estimates is most pronounced. In data-sparse regions, particularly the southern United States, the Bayesian framework shows enhanced signal clarity and spatial consistency compared to MLE, which tends to suppress topographic and climatological signals. The Bayesian framework additionally provides full posterior distributions, enabling credible interval estimation that transparently communicates parameter uncertainty.
This methodology provides defensible tail risk estimates for stochastic winter storm models and demonstrates applicability to other sparse extreme event problems.
How to cite: Ansari, M. S., Ait-Chaalal, F., Dobbin, A., Ali, M., and Zhao, A.: Towards Robust Tail Risk Estimation for Freezing Rain Hazard: A Bayesian Extreme Value Approach, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11495, https://doi.org/10.5194/egusphere-egu26-11495, 2026.
Understanding the Mediterranean Sea heat budget is crucial for assessing regional climate variability and warming responses. In this work, we analyse the spatio-temporal structure of heat budget components using atmospheric (ERA5) and ocean reanalysis (ORAS5). Heat budget analyses are compared to sea surface temperature (SST) and salinity (SSS), total water column ocean heat content (TOHC), and complemented by heat fluxes at the atmosphere-ocean interface (Qnet) and oceanic advective terms. Climatological SST reveals a strong west-east gradient, with the Levantine Basin exhibiting the highest temperatures. TOHC is maximal in the eastern region and lower in shallow basins such as the Adriatic and Gulf of Lion. SSS increases from 35–37 PSU in colder and deeper basins in the western part of the Mediterranean to values in excess of 40 PSU in the Levantine Sea, due to positive evaporation and stratification. Net fluxes at the interface range from winter heat loss (-150 to -200 Wm⁻²) to summer heat gain (+150 to +200 Wm⁻²), with maximum variability in the eastern Mediterranean. Preliminary trend analysis indicates steady increments in TOHC and SSS since the 1980s, with accelerated heat accumulation in the Eastern Mediterranean. An EOF analysis of monthly TOHC anomalies reveals a dominant basin-wide warming mode and secondary east-west dipole structures connected with regional circulation features. The role of advective fluxes in determining these regional circulation features is discussed.
Keywords: Mediterranean Sea, Spatio-temporal analysis, Heat budget components, Seasonal variability, Decadal trends, EOF analysis.
How to cite: Kumar, S., Bordoni, S., Lembo, V., and Nyongesa, A. M.: Dominant Spatio-Temporal Modes of Mediterranean Heat Budget Variability, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14430, https://doi.org/10.5194/egusphere-egu26-14430, 2026.
The Mediterranean climate regions (MCRs) of the world, including the west coast of North America, central Chile, the far southwest tip of Southern Africa and southwest Australia, are characterized by temperate, wet winter and warm (or hot) dry summer, and they are typically located on the western edge of continents in the subtropics to mid-latitude sectors. In a previous work, adopting a probabilistic approach and using CMIP5 21st century projections, we quantified the risk of a poleward shift of MCRs, mostly over the Mediterranean region and western North America, with their equatorward margins replaced by arid climate type.
Following on from the above and exploiting newly available CMIP6 simulations and sensitivity experiments, we have designed an updated assessment of future climate changes in MCRs. The objective is to identify how MCRs are projected to change in terms of hydroclimate conditions, as they all are transitions areas between wet and dry climates. Future projections indicate an increased probability of a MED climate-type poleward, while a reduced probability of this direction of change is projected equatorward (mostly evident in Northern Hemisphere MCRs and over South America). Over South Africa and Southern Australia a reduced probability to have MED climate-type is evident as well but the continents do not extend much poleward to clearly assess this change. In addition to the overall picture of hydroclimate changes in these regions with commonalities and differences as expected from current dynamical understanding, we have designed an evaluation of the uncertainties in the projections and estimates of the models’ reliability in representing observed past changes.
How to cite: Cherchi, A., Alessandri, A., Possega, M., Senigalliesi, V., and Renwick, J.: Future changes and associated uncertainties over the Mediterranean Climate Regions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19239, https://doi.org/10.5194/egusphere-egu26-19239, 2026.
Compound flooding arises from the interaction of multiple flood drivers, particularly hydrologic and oceanographic drivers such as extreme precipitation (P) and elevated sea level or storm surge (SL/SS). These interconnected drivers often share common climate influences, and when they occur simultaneously or in close succession, the resulting joint probability of flooding can be substantially higher than under the assumption of independence. In this study, a bivariate non-stationary flood frequency analysis framework is developed to assess compound flooding risks along the Indian coast. The dependencies between precipitation and sea level/storm surge are modeled using copula-based approaches, while Bayesian inference is employed for parameter estimation of both marginal distributions and copula functions under non-stationarity. This enables robust uncertainty quantification while incorporating the influence of changing climate and ocean conditions. Joint return periods are evaluated for different compound flood scenarios (e.g., AND and OR cases), enabling a more realistic characterization of coastal hazard likelihood. Additionally, failure probabilities (FPs) are estimated to reflect the chance that at least one driver exceeds its critical threshold within standard infrastructure design lifetimes. The results highlight the importance of accounting for temporal changes and interdependence between precipitation and sea level/storm surge in coastal flood risk assessment. The findings provide actionable guidance for selecting resilient design criteria and support informed decision-making for coastal flood protection and long-term risk management.
How to cite: Mohseni, U., Rajendran, V., and Khouakhi, A.: A Bayesian Non-Stationary Framework for Bivariate Compound Flood Risk Assessment Along the Indian Coast, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-740, https://doi.org/10.5194/egusphere-egu26-740, 2026.
Drylands forestation, a component of earth sciences, ecology, and ecosystems, offers the potential for long-term sequestration of atmospheric CO2. Israel’s Yatir Forest is a 28 km2 planted semi-arid Aleppo pine forest successfully growing with no irrigation or fertilization and only 280 mm average annual precipitation. Yatir’s organic carbon sequestration (OCS) rate was measured as ~550 g CO2 m-2 yr-1 (150 g C) carbon. This value was obtained using the data of a 15 year long monitoring program that combined eddy covariance (EC) flux measurements, as well as carbon stock counting inventories. In addition, based on Yatir’s measured inorganic carbon sequestration (ICS) rate, an additional 216 g CO2 m−2 yr−1 globally may be sequestered via calcite (CaCO3) precipitation in soil. The above OCS ad ICS rates are assumed here to be representative of global drylands. Part of this ICS is related to root and microbial exhalation of CO2. A tree’s roots exhale CO2 into the soil after some of the tree’s glucose (produced by photosynthesis) has been oxidized to supply energy for the tree’s cellular processes. Exhaled CO2 combined with soil H2O forms soil carbonic acid (H2CO3); and then bicarbonate (HCO3-) which combines with soil Ca2+ to form calcite. Another part of the ICS comes from soil microbes that use extracellular polymeric substances (EPS) to directly precipitate calcite. Low rainfall in drylands precludes dissolving the precipitated calcite. The potential maximal efficacy of global forestation for reducing global warming and ocean acidification depends on the maximal area available for sustainable forestation. The dominant limitation, particularly in the vast drylands regions, is the apparent lack of water. This would reduce the potential area for sustainable forestation to a published estimate of roughly 4.5 million km2, ~10% of global hot drylands. However, in most drylands areas, plentiful water is available from immediately underlying local paleowater (fossil) aquifers. Using such water, until now not previously taken into consideration, conservatively yields a functional dryland forestation area of ~9.0 million km2. Measurements at Yatir show that drip irrigation to 18% average Soil Moisture (higher than the rainfed 12% SM) would approximately double the OCS and ICS rates. In addition, the tree density could be increased, which would independently double the organic carbon sequestration rate. The potential total annual sequestration rate is then conservatively estimated as 20.0 Gt CO2 yr−1, divided between 14.0 Gt CO2 yr−1 (organic) and 6.0 Gt CO2 yr−1 (inorganic). This corresponds to 100% of the annual rate of atmospheric CO2 increase. Significantly, this quantity removed from the atmosphere would also reduce ocean acidification. Note however that the transformation of bright high albedo deserts to darker forests could reduce the positive projected climate cooling effects attained by as much as ~25%. The effective reduction may be less, considering that increased forestation evapotranspiration would decrease surface temperature; and increase albedo via increased cloud cover. Our sequestration estimate demonstrates the global potential, the need for further measurements, and the need to begin implementing a global land management policy of widespread tree planting in drylands regions.
How to cite: Moinester, M. and Kronfeld, J.: Potential Global Sequestration of Atmospheric Carbon Dioxide by Drylands Forestation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2084, https://doi.org/10.5194/egusphere-egu26-2084, 2026.
California’s water system is among the most complex and engineered in the world, spanning vast geographic, climatic, and institutional scales. Its two major interlinked conveyance networks, the State Water Project (SWP) and the Federal Central Valley Project (CVP), collect, store, and transport water over ~1000 km from northern headwaters to southern agricultural and urban centers. Together, they sustain irrigation for >1.2 million ha of farmland and provide drinking water for more than 23 million people. However, these systems—originally designed in the mid-20th century—now face mounting challenges from climate change, ecosystem degradation, and groundwater depletion. Reduced snowpack, intensifying droughts, and shifting precipitation patterns strain both surface and subsurface storage, with cascading consequences for the state’s energy, agriculture, and ecological resilience. Substantial groundwater losses due to agricultural pumping during droughts (up to ~15,000 cubic hectom), highlighting the urgency of sustainable management. Implementation of the Sustainable Groundwater Management Act (SGMA) and investments in drought resilience innovation programs represent critical steps toward adaptation. Yet, balancing competing demands among agricultural, urban, and environmental sectors remains a formidable task. This seminar explores these ‘basics’ of California water and just some of the many technical, ecological, and policy dimensions of California’s water infrastructure under climate stress, including interdependencies between energy use, biodiversity, and water supply reliability. By integrating hydrological science with adaptive governance, California’s water future offers a global case study in managing scarcity within complexity. What can we learn from other countries in similar situations?
How to cite: Blumenshine, S.: California Water Supply & Distribution Basics; Context for Climate & Drought Resilience, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15177, https://doi.org/10.5194/egusphere-egu26-15177, 2026.
Simulations from the Large Ensemble Single Forcing Model Intercomparison Project are used to isolate the impact of greenhouse gases (GHGs) and anthropogenic aerosols for historical (1850-2014) wintertime drying in the Mediterranean region.
Increasing GHGs have already led to a clear ridging signal across the Mediterranean and a precipitation reduction of up to 15%. Anthropogenic aerosols, on the other hand, led to Mediterranean troughing in most models and hence cancelled out much of the GHG induced signal. The net effect when all forcings are present is a weak drying, and this weak drying and subtle ridging is consistent with recent observational evidence that the anthropogenically forced wintertime drying in the Mediterranean region has not yet robustly emerged. There is pronounced intermodel spread in both the sea level pressure and precipitation responses to both GHGs and aerosols, however, and the relation between this spread and the spread in 9 different climatic metrics is explored to help clarify dynamical mechanisms and the causes of intermodel spread. A stronger tendency towards Mediterranean ridging is found in models and ensemble members with a more pronounced North Atlantic warming hole, a stronger stratospheric polar vortex, and to a lesser degree with a larger poleward shift of the eddy-driven jet. While these three sensitivities are as expected, others are not. Namely, a larger increase of global mean temperature is associated with troughing over the Mediterranean, opposite to naive expectations. Moreover, the single-forcing experiments indicate that a warmer land relative to the ocean (over the Mediterranean) is associated with troughing, rather than the previously proposed ridging. Other sensitivities are weak: the spread in the historical response cannot be explained by spread in shifts of the Hadley cell edge or the zonal-mean subtropical jet. Overall, the results of this work highlight that aerosols have influenced Mediterranean climate in the historical climate and helped mitigate the greenhouse gas induced drying.
How to cite: Avisar, D. and Garfinkel, C.: Revisiting the Historical Wintertime Drying of the Mediterranean in the LESFMIP Simulations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16062, https://doi.org/10.5194/egusphere-egu26-16062, 2026.
