By highlighting the complementary nature of physical intuition and mathematical formalism, this session seeks to advance our understanding of the processes that give rise to extremes, improve predictive capabilities, and assess the extremes' societal and environmental impacts.
Topics of interest include, but are not limited to:
- Variability and projected changes in extremes under climate change
- Representation and performance of climate models in simulating extreme events
- Attribution of extreme events
- Emergent constraints on extreme behavior
- Predictability of extremes across meteorological to climate timescales
- Connections between extremes in dynamical systems and observed geophysical extremes
- Theoretical and applied studies of extremes in nonlinear and chaotic systems
- Downscaling techniques for extreme events
- Linking the physical dynamics of extreme events to their impacts on society and ecosystems.
We particularly encourage submissions that bridge disciplines, propose novel methodologies, or offer new insights into the mechanisms and consequences of extreme geophysical phenomena. We encourage submissions from the "Transdiscipinary Newtork to bridge Climate Science and Impacts on Society" (FutureMED) and the "Seasonal-to-decadal climate predictability in the Mediterranean: process understanding and services" (MEDUSSE) COST action communities.
Orals: Wed, 6 May, 08:30–15:45 | Room -2.21
The frequency and duration of hot extremes is projected to increase over the coming decades. It remains, however, unclear to what extent persistent surface temperature extremes require an anomalously persistent circulation in the upper troposphere. To shed more light on this relationship, we combine idealized model experiments with reanalysis data and assess the zonal phase speed of Rossby waves as a proxy for circulation persistence. In particular, we compare the climatological-mean phase speed spectrum to the properties of heatwave-generating Rossby wave packets.
In the idealized model without thermodynamic feedbacks, a phase speed increase in response to a localized thermal forcing reduces the frequency of heatwaves. Reanalysis data for the Southern hemisphere mid-latitudes shows a similar and significant phase speed increase from the 1980s until today. However, the observed mean phase speed increase does not apply to heatwave-generating Rossby waves and hence does not contribute to a change in heatwave frequency. The Northern hemisphere, on the other hand, does not yet show a clear phase speed trend in reanalysis. But with continued global warming, we expect an acceleration of heatwave-generating Rossby waves and a reduced upper-tropospheric forcing to persistent temperature extremes in the future.
How to cite: Wicker, W., Russo, E., and Domeisen, D.: Heatwave-generating Rossby waves and the persistence of temperature extremes in a changing climate, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3128, https://doi.org/10.5194/egusphere-egu26-3128, 2026.
Wintertime stratospheric circulation in the Northern Hemisphere is dominated by a strong and persistent westerly polar vortex. However, every one to two years, this system undergoes a strong disruption associated with a fast deceleration or even a reversal, accompanied by a massive warming of the polar stratosphere. The tropospheric impacts of these extreme events, commonly referred to as “sudden stratospheric warmings” (SSWs) are well documented, but their precursors and subsequent responses in the troposphere remain frustratingly difficult to categorize systematically. Using recent advances in dynamical systems theory applied to the atmosphere, we analyze from a general point of view, the relationship between very anomalous stratospheric states and tropospheric configurations. We find that highly anomalous geopotential configurations at 10 hPa are unequivocally associated with the occurrence of a strong stratospheric vortex deceleration. However, no distinctive tropospheric patterns can be identified either prior to or following these events. This suggests that both tropospheric precursors and responses to extreme vortex decelerations are fundamentally nonspecific and in consequence, they could be statistically indistinguishable from the background tropospheric variability.
How to cite: Gallego, D., Álvarez-Castro, C., Faranda, D., and Peña-Ortiz, C.: Can tropospheric configurations linked to the onset or aftermath of polar vortex decelerations be distinguished from climatology?, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5518, https://doi.org/10.5194/egusphere-egu26-5518, 2026.
Extreme stratospheric polar vortex events, including sudden stratospheric warmings (SSWs) and episodes of strong polar vortex, are known to influence wintertime surface weather by modulating large-scale circulation patterns. While previous studies have primarily focused on their impacts over the North Atlantic and northern Europe, the effects on Mediterranean storm activity remain less well quantified. In this study, we examine the tropospheric response to SSW events from 1979 to 2020, with a particular focus on the associated changes in cyclone activity over the Mediterranean region.
Using a composite analysis of 28 SSW events within the study period, we examine the temporal and spatial evolution of cyclone frequency, genesis density, and associated dynamical fields before and after SSW onset. Seasonal and daily climatological signals are removed to isolate anomalies directly linked to stratosphere-troposphere coupling. Our results show a clear increase in cyclone activity over North Africa and the Atlantic coast of the Iberian Peninsula, associated with increased precipitation over western and southern Europe following SSW events. This is consistent with a southward displacement of the midlatitude jet and storm track. This shift is supported by enhanced upper-level wind speeds, divergence, and potential vorticity anomalies over the region during the post-SSW 2-month period. Despite the robust composited signal, substantial inter-event variability is observed, indicating that not all SSWs lead to an identical response. These findings highlight the importance of event-to-event differences in determining regional storm impacts.
Overall, this study demonstrates that stratospheric polar vortex disruptions can significantly modulate Mediterranean storms on subseasonal timescales, highlighting the potential value of stratospheric information for enhancing the predictability of wintertime extreme weather over southern Europe and the Mediterranean Basin.
Keywords: Sudden stratospheric warming; polar vortex; Mediterranean cyclones; jet stream; stratosphere–troposphere coupling; subseasonal variability
How to cite: Jangir, B., Álvarez-Castro, C., Peña Ortiz, C., Gallego Puyol, D., Raveh-Rubin, S., and Strobach, E.: Impact of Sudden Stratospheric Warming on the Genesis of Mediterranean Cyclones and Associated Precipitation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13596, https://doi.org/10.5194/egusphere-egu26-13596, 2026.
Mediterranean tropical-like cyclones, known as medicanes, are mesoscale systems that develop over the Mediterranean Sea and exhibit structural similarities to tropical cyclones, despite forming under markedly different environmental conditions. Air–sea interactions play a key role in their development and intensification, yet the behaviour of sea surface temperature (SST) before, during, and after medicane events remains insufficiently quantified.
In this study, we analyse SST anomalies and daily SST variability associated with medicane events using the Copernicus high-resolution Level-4 reprocessed Sea Surface Temperature dataset. Daily SST fields and their day-to-day variations are examined along medicane tracks and surrounding areas and compared against climatological references to assess the SST response to medicane passage. The analysis accounts for differences related to seasonality, medicane development stage, and formation region within the Mediterranean basin.
Results reveal marked SST anomalies associated with medicane events, with a consistent reduction in daily SST and a pronounced negative anomaly in daily SST variation along the medicane track. The magnitude and spatial extent of these anomalies vary depending on the season and phase of the medicane life cycle, indicating distinct air–sea interaction regimes across different Mediterranean sub-basins. The observed SST cooling is consistent with enhanced surface fluxes and upper-ocean mixing induced by medicane-related wind forcing.
These findings highlight the role of SST anomalies and short-term SST variability in the evolution and intensification of medicanes and provide new insights into the coupled ocean–atmosphere processes governing these systems. Improved understanding of SST–medicane interactions is essential for better representation of medicane-related hazards and for assessing their potential impacts in a warming Mediterranean, where socio-economic exposure and vulnerability are increasing.
How to cite: Pastor, F., Pardo-García, D., and Khodayar, S.: Sea surface temperature anomalies associated with Mediterranean tropical-like cyclones , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18955, https://doi.org/10.5194/egusphere-egu26-18955, 2026.
Extreme precipitation over Europe is often linked to large-scale atmospheric circulation anomalies, yet it remains unclear which dynamical features recur systematically across many independent events, and how their influence evolves with time and altitude. In particular, the extent to which coherent, large-scale dynamical structures act as precursors to extreme rainfall has not been quantified so far beyond traditional composite-based approaches.
Here, we introduce a lagged coupled climate-network framework to investigate the interdependency between extreme precipitation events and atmospheric circulation from a functional climate network perspective. Extreme precipitation events are identified from ERA5 precipitation data by applying a local percentile threshold to daily precipitation sums and represented as binary event series, while two-dimensional fields of additional variables in different atmospheric layers—including geopotential height, relative vorticity, and temperature at multiple pressure levels—are treated as continuous variables. Using point-biserial correlation as statistical association measure between these different types of time series, we construct lagged event–field coupled networks that explicitly distinguish positive and negative statistical associations. Network connectivity is quantified through the cross-degree, which measures how many grid points of surface extreme events are significantly linked to a given atmospheric grid point (and vice versa), thereby emphasizing the recurrence and spatial relevance of circulation features rather than their correlation strength alone.
Our analysis reveals a coherent temporal evolution and vertical structure of circulation coupling to hydrometeorological extremes at the surface. At negative lags, cross-degree patterns are dominated by mid- to upper-tropospheric geopotential height and vorticity anomalies, indicating the recurrent presence of large-scale dynamical features prior to extreme precipitation events. With increasing lag, the coupling progressively shifts toward lower tropospheric levels, suggesting a transition from large-scale circulation influences before the events to near-surface circulation imprints afterward. Spatially, regions of enhanced cross-degree exhibit a systematic west-to-east displacement with changing lag, extending from the western North Atlantic and Greenland sector toward continental Europe. This spatial progression is consistent with downstream evolution along the North Atlantic–European circulation corridor. A pronounced and recurrent signal over the British Isles emerges across multiple variables, highlighting this region as a dynamically relevant area in the large-scale circulation context of European precipitation extremes.
By explicitly quantifying where, when, and at which vertical levels circulation anomalies of the same type recur across many extreme events, our coupled network approach provides a complementary perspective to conventional correlation and composite analyses. Our results demonstrate the potential of coupled functional climate networks to identify robust, recurring circulation patterns associated with extreme precipitation, offering new insights into precursor dynamics, vertical coupling, and large-scale organization of midlatitude extremes without assuming a specific underlying mechanism.
How to cite: Bishnoi, G. and V. Donner, R.: Lagged Coupled Climate Networks for Identifying Recurrent Circulation Patterns Behind Extreme Rainfall in Europe, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18041, https://doi.org/10.5194/egusphere-egu26-18041, 2026.
Climate extremes, including heatwaves, extreme precipitation, tropical cyclones, and related hazards, pose significant risks to society and ecosystems.
Recent advancements in observational techniques, numerical modeling, theoretical frameworks, and AI methods have greatly improved our understanding and prediction of these extremes. However, despite significant progress, key challenges remain unresolved, particularly in achieving a thorough understanding of the physical drivers of extreme events, improving the transparency of AI-based prediction methods, and evaluating the vulnerability and resilience of cities to their impacts. To address these challenges, we present various approaches drawn from different fields, including dynamical systems theory, explainable AI, and NLP-based methods. Given the flexible and generalizable nature of these methods, we believe they may pave the way toward more robust solutions for addressing the challenges posed by climate extremes.
How to cite: Dong, C. and Mengaldo, G.: Interdisciplinary Approaches in the Study of Climate Extremes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18393, https://doi.org/10.5194/egusphere-egu26-18393, 2026.
Predicting spatiotemporal extreme events using dynamical systems theory poses several major challenges. One of these is the phase space dimensionality of spatiotemporal systems. Extreme events are rare, while the number of variables that could potentially drive them is large. Often, a subset of the phase space is sampled, or features are engineered based on previous research on drivers, to predict spatiotemporal extreme events. On the other hand, the background attractors are often assumed to be of much smaller dimensionality than the phase space. Therefore, we propose a novel framework that approximates the background attractor of chaotic systems using an autoencoder. On this lower-dimensional attractor representation, precursor densities are created from historical analogues. Based on these precursor densities, predictions of extreme events are made. This framework proves to be efficient in predicting extreme events in a simplified turbulent flow and a climate model. Without engineering-specific predictor feature sets, this lower-dimensional representation of the attractor allows for more efficient and accurate analog prediction of extreme events in large chaotic systems.
How to cite: Schuurman, K. R., Dwight, R. P., and Doan, N. A. K.: Predicting extreme events by identifying precursors on the chaotic attractor manifold, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20508, https://doi.org/10.5194/egusphere-egu26-20508, 2026.
Using ERA5 re-analysis data, 1950 to 2024, we look at surface temperature extremes, which we define as regions of at least 0.5 million square kilometers where the monthly mean 2m temperature exceeds its 25 year climatological mean by at least 1.5 standard deviations. While heat extremes are overall a topic of intense research, we here target a facet of such extreme events that has been less examined so far: how they manifest in terms of top of atmosphere (TOA) radiative fluxes. For the short- and long-wave TOA fluxes associated with such extreme events, we find typically enhanced values. This may be expected, given that mid-latitude heat waves are often accompanied by clear skies. For the TOA net energy flux, we find typically negative values. Spatially more extended extreme events tend to be associated with stronger temperature anomalies. Individual extreme events may deviate from these general tendencies. For selected extremes, daily ERA5 re-analysis data are examined. For the period 2001 to 2024, TOA fluxes from ERA5 re-analysis are compared to CERES satellite data.
How to cite: Folini, D. and Domeisen, D.: Surface temperature extremes mirrored in top of atmosphere radiative fluxes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13622, https://doi.org/10.5194/egusphere-egu26-13622, 2026.
Future changes in mean climate and extremes have been extensively assessed using model simulations of the 21st century under varying levels of anthropogenic greenhouse gas (GHG) forcing. Here, we examine the long-term climate legacy of an idealized abrupt stabilization of present-day and near-future GHG concentrations, with a focus on summer heatwaves across the Northern Hemisphere. Our analysis is based on multicentennial simulations performed with the EC-Earth3 model, in which external forcing is held fixed in time. After several centuries of internal adjustment, the climate system approaches a quasi-equilibrium state characterized by a stable level of global warming that depends strongly on the timing of forcing stabilization. Crucially, far-future quasi-equilibrium conditions can differ substantially from those that would arise if the same warming levels were reached by the end of the century, reflecting the distinct roles of fast and slow components of the Earth system. A key feature of the quasi-equilibrium response is a partial recovery of the Atlantic Meridional Overturning Circulation relative to transient simulations, which influences regional climate and leads to a pronounced amplification of heatwave frequency and intensity over the North Atlantic sector. Conversely, many land areas ultimately experience less severe heatwaves than in transient scenarios, owing to the slower warming rates in the stabilization experiments. Results show that the long-term response of extremes is shaped by the magnitude of global warming, as well as the pathway and timescale over which that warming is realized, highlighting the need for equilibrium-focused experiments in future climate risk assessments.
How to cite: Corti, S., Simolo, C., Rozenberg, L., Meccia, V., and Fabiano, F.: Heatwave response in quasi-equilibrium versus transient climate scenarios, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19395, https://doi.org/10.5194/egusphere-egu26-19395, 2026.
In recent decades, the Euro–Mediterranean region has experienced a marked increase in catastrophic summer climate extremes, including persistent record-breaking atmospheric and marine heatwaves, and destructive convective events such as long-lived mesoscale convective systems (derecho) and supercells with unparalleled hail-size. All these have provoked severe socioeconomic, ecological and human impacts. While these phenomena are often studied separately, their frequent co-occurrence suggests the influence of common large-scale circulation drivers, which remain actively debated.
Building on recent work linking North Atlantic freshwater anomalies to downstream atmospheric circulation responses, this ongoing study explores whether part of the recent European summer climate signal may be influenced by remote hemispheric-scale forcing associated with Greenland Ice Sheet mass loss, which has also coincidentally accelerated in recent decades due to anthropogenic influences. This linkage was not initially targeted but emerged unexpectedly from exploratory diagnostics motivated by broader investigations of North Atlantic variability. Preliminary results indicate that periods of enhanced summer Greenland melt tend to coincide with subsequent anomalous spring–summer circulation patterns over the Euro-Atlantic sector that favour persistent ridging and blocking-like conditions over the Euro-Mediterranean region. Such circulation states are consistent with environments conducive to prolonged heat stress, the development of marine heatwaves, and subsequent severe convective outbreaks.
Initial comparisons with global climate models from CMIP6 suggest that this potential pathway is poorly represented, possibly due to limitations in simulating localized freshwater forcing and its coupled atmosphere–ocean effects, which indicates that current projections of future climate may be underestimating these impacts. Our findings would point out Greenland melting as a previously unreported major driver of spring-summer large-scale circulation changes. Incorporating these processes could then be essential for forecasts systems and long-term projections, likely posing a significant gap in our ability to project future risk. Ongoing work focuses on testing the robustness of this emerging signal, clarifying its relevance relative to other known drivers of European summer extremes and exploring its hemispheric-scale reach.
How to cite: González-Alemán, J. J., Oltmanns, M., González-Herrero, S., Vitard, F., Donat, M., Doblas-Reyes, F., Barriopedro, D., Riboldi, J., Calvo-Sancho, C., Jiménez-Esteve, B., Cos, P., and Wehner, M.: Emerging evidence of Greenland Ice Sheet melt influence on recent Euro-Mediterranean record-breaking heat and convective storms, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14086, https://doi.org/10.5194/egusphere-egu26-14086, 2026.
Heat and drought extremes pose escalating socio-economic and ecological risks, yet the most severe combinations of these high-impact extremes possible today remain poorly understood. Using thousands of plausible ensemble-boosting current climate storylines, we reveal the risk for more intense drought compounding with far more extreme heat and fire weather than ever experienced over Europe in the recent past. The most extreme boosted heatwaves surpass historical extremes in both intensity and particularly in persistence, and also exceed levels considered extreme in a 3°C warmer world by large margins. Some of the most extreme heatwaves arise under severe soil moisture depletion, while others develop under strong surface temperature gradients in the North Atlantic and extreme heat in the nearby Mediterranean and Atlantic basins, underscoring the diversity of pathways to worst-case conditions. Furthermore, our work reveals an additional risk: worst-case heatwaves occur predominantly after another extreme heatwave. This highlights the potential for aggravated impacts due to decreased recovery times and intensified heat stress on humans, ecosystems and infrastructure made more vulnerable by the first event. Given the scale, intensity, and unprecedented successive and compounding nature of these worst-case storylines, we underscore the urgent need for well-informed adaptation strategies that sufficiently reflect these risks.
How to cite: Suarez-Gutierrez, L., Beyerle, U., Mittermeier, M., Vautard, R., and Fischer, E. M.: Worst-Case European Heat and Drought Storylines generated using Ensemble Boosting, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21564, https://doi.org/10.5194/egusphere-egu26-21564, 2026.
Global warming is projected to intensify the hydrological cycle, amplifying risks to ecosystems and society. While extreme rainfall appears to exhibit stronger sensitivity to global warming compared to mean rainfall rates, a unifying physical mechanism capable of explaining this systematic divergence has remained elusive. Here, we integrate theory and data from a global network of nearly 50,000 rain-gauge stations to unravel the rainfall intensity and frequency response to rising temperatures. We show that the distributions of wet-day rainfall depth exhibit self-similar shapes across diverse geographical regions and time periods. Combined with the temperature response of rainfall frequency, this consistently links mean and extreme precipitation at both local and global scales. We find that the most probable change in rainfall intensity follows Clausius-Clapeyron (CC) scaling with variations shaped by a fundamental hydrological constraint. This behavior reflects a dynamic intensification of updrafts in space and time, which produces localized heavy precipitation events enhancing atmospheric moisture depletion and hydrologic losses through runoff and percolation. The resulting reduction in evaporative fluxes slows the replenishment of atmospheric moisture, giving rise to the observed trade-off between rainfall frequency and intensity. These robust scaling laws for rainfall shifts with temperature are essential for climate projection and adaptation planning.
How to cite: Yin, J., Gao, B., and Porporato, A.: Scaling of Rainfall Intensity and Frequency with Rising Temperatures, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-22751, https://doi.org/10.5194/egusphere-egu26-22751, 2026.
The Eastern Mediterranean is a well-established climate change hotspot, where intensifying hydrological extremes increasingly translate into high-impact weather conditions with cascading societal consequences. While long-term changes in mean atmospheric moisture are relatively well documented, much less is known about the evolution of extreme moisture states that act as precursors to severe precipitation, flooding, and compound hydroclimatic hazards.
In this study, we investigate the extreme behaviour of precipitable water vapour (PWV) using homogenised, high-frequency GNSS-derived observations from a dense network located in the Eastern Mediterranean transition zone. To ensure climate-quality consistency, the dataset was processed following internationally recognised standards, including IGS Repro3 strategies, covering the period 2000–2019. Moving beyond conventional trend-based analyses, we employ a non-stationary Extreme Value Theory (EVT) framework, combining Generalised Extreme Value (GEV) and Peak-Over-Threshold (POT) approaches to characterise the tails of the PWV distribution. This enables an assessment of changes in the magnitude, frequency, and persistence of rare moisture extremes under ongoing warming, independent of mean climatological shifts.
Return levels corresponding to different recurrence intervals are estimated to provide observational constraints on extreme atmospheric moisture scaling and its consistency with theoretical Clausius–Clapeyron expectations. The statistical results are further interpreted in the context of large-scale atmospheric drivers using ERA5 reanalysis data, shifting the focus from describing atmospheric states to identifying weather conditions conducive to high-impact hydroclimatic outcomes.
This contribution directly aligns with the objectives of the FutureMed COST Action (CA22162) by bridging physical climate processes, advanced statistical characterisation of extremes, and impact-relevant indicators of risk. By focusing on extreme moisture states rather than mean conditions, the study supports a shift from describing what the atmosphere is to assessing what weather conditions are likely to do in terms of hydroclimatic impacts, thereby improving the understanding and predictability of high-impact weather in the Eastern Mediterranean region.
How to cite: Zengin Kazancı, S.: Unveiling the Tails of Atmospheric Moisture Extremes in the Eastern Mediterranean: Non-Stationary GNSS-Based Evidence for High-Impact Hydroclimatic Conditions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16534, https://doi.org/10.5194/egusphere-egu26-16534, 2026.
Floods associated with extreme precipitation cause tremendous damage and losses every year, and are projected to become more frequent and more severe with climate change in most land regions. Events of much higher intensities than previously observed can cause unforeseeably large impacts due to their unprecedentedness. The changing occurrence probability of such “surprise events” is closely related to changes in the statistical distribution of extreme precipitation: while a constant scaling with temperature (such as Clausius-Clapeyron) causes a constant fractional increase for all return levels, strong increases in the variability of extreme precipitation (distribution width) lead to relatively stronger intensification of the most extreme events. The latter change is indicative of increasing high-impact surprise event probabilities. Regions where rare extremes exhibit a faster relative intensification than moderate extremes (skewed intensification) are subject to RAINE: Rareness-Amplified INtensification of Extremes. In other words, RAINE means the worst events get worse the fastest.
We present a statistical framework based on extreme value theory to diagnose RAINE in annual maximum daily precipitation (Rx1d) from observations and simulations. We focus in particular on results from the 10-member high-resolution (0.25° atmosphere/land and 0.1° ocean) CESM1 ensemble (MESACLIP, historical+RCP8.5), which has been shown to simulate Rx1d quite accurately. We identify a strong RAINE-effect for most of the global land over the 21st century under RCP8.5. We categorise the data based on region and Rx1d-causing weather phenomenon, and find that a physical scaling based on vertical updraft and relative humidity explains the RAINE pattern. Different seasons, regions and phenomena feature different relative contributions of vertical updraft and relative humidity to RAINE, which can be linked to different environmental conditions and climate change effects governing Rx1d changes. In observations, robust distributional changes are difficult to detect due to high variability of extreme precipitation. Our combined statistical and physical characterisation of RAINE can help explain and constrain uncertainties in future risks posed by unprecedented extreme precipitation.
How to cite: de Vries, I., Castruccio, F., Fu, D., and O'Gorman, P.: Rareness Amplified INtensification of Extreme rainfall (RAINE): how the worst events get worse the fastest, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19415, https://doi.org/10.5194/egusphere-egu26-19415, 2026.
Extreme precipitation exhibits pronounced local variations associated with dynamic and thermodynamic changes on synoptic and regional scales under global warming inducing important impacts over main socioeconomic sectors such as agriculture, tourism, health and energy. Local-to-regional variations in extreme precipitation are especially marked on climate change hotspots, such as the Iberian Peninsula, reflecting the complex transition between Atlantic and Mediterranean climate influences and further hindering an accurate assessment of climate change impacts and the development of effective adaptation strategies. Therefore, it is crucial to identify variations in atmospheric dynamics as main drivers of changes in the characteristics of extreme precipitation events (EPEs) on subregional scales to better determine the areas subject to specific changes and improve our understanding of extreme weather events to enhance predictability.
In this context, this study conducted a comprehensive analysis using a precipitation regionalization approach with a high resolution (~5 km) gridded dataset for the period 1951-2021 obtaining 8 precipitation-coherent regions in the Iberian Peninsula. EPEs were characterized over each region, and their evolving atmospheric drivers were identified using an objective synoptic classification method with ERA5 data. Besides, an analysis of variations in EPEs intensity and frequency, as well as changes in the associated synoptic conditions and atmospheric water vapor distributions were assessed.
Our results revealed a generalized mean intensification of EPEs for the study period. Nevertheless, we highlight two different pathways: (i) Atlantic regions presenting a moderate (5-10 %) intensification of extreme precipitation linked to an increase of surface flows and counterposing the observed weakening or northward displacement of upper-level perturbations, and (ii) Mediterranean regions showing a marked (15-25 %) extremization of EPEs associated with vorticity intensification at 500 hPa. Besides, these variations occur alongside an atmospheric moistening (up to 6 mm in the Ebro region) of the moistest air masses denoting the highly complex interplay between thermodynamic and dynamic factors. We emphasize the importance of regionalized approaches to enhance our comprehension on extreme precipitation over regions with complex topography and, more importantly, the corresponding implications on early warning systems and efficient climate adaptation strategies in climate change hotspots.
How to cite: Benetó, P., Valiente, J. A., and Khodayar, S.: Understanding Shifts in Extreme Precipitation and Synoptic Forces in a Regionalized Framework: The Iberian Peninsula, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18626, https://doi.org/10.5194/egusphere-egu26-18626, 2026.
The late-October 2024 flooding in Valencia (eastern Spain) was triggered by an exceptional extreme precipitation event (EPE) associated with a quasi-stationary cut-off low over the western Mediterranean. In this study, we assess the meteorological exceptionality of the October 2024 event by combining a basin-scale, percentile-based catalogue of rainfall extremes with a multi-level diagnosis of thermodynamic and dynamical atmospheric drivers.
Extreme precipitation is analysed using the dense SAIH rain-gauge network covering the Júcar River Basin at hourly and 5-minute temporal resolution for the period 1990–2024. Hourly p99 precipitation thresholds are computed for each station using an autumn (September–November) rolling-hour climatology. Local exceedances above p99 are aggregated into a basin-wide “overall magnitude” index (M), which integrates intensity and spatial footprint. EPEs are identified as continuous periods with M > 0 and ranked according to duration, peak intensities at 1-, 3-, 6-, 12- and 24-hour accumulation periods, cumulative local magnitude, mean excess above threshold, and the number of affected stations. The October 2024 event is contextualised against (i) the seven most extreme autumn EPEs (>p99) over the last three decades and (ii) a broader set of extreme but non-record events (p90–p99).
To link hydrometeorological extremeness with atmospheric drivers, we analyse the 1–96 h period preceding peak precipitation using 3-hourly CERRA reanalysis fields from 1000 to 100 hPa. Diagnostics include integrated water vapour (IWV), vertical humidity and water vapour profiles over peak-impact areas, absolute vorticity, and wind shear across multiple pressure-layer pairs.
Results show that the October 2024 event ranks as the most extreme autumn EPE in the record, with an unprecedented cumulative local magnitude of 4392 mm, nearly twice that of the second-ranked event (2275 mm in October 2000). The event is characterised by exceptionally high IWV values (~40 mm) over the affected region and a rapid IWV increase of approximately 0.4 mm h⁻¹ (around 25 mm in less than 72 h) prior to peak intensity. In addition, very strong vertical wind shear exceeding 25 m s⁻¹ between the surface and 400 hPa favoured sustained convective organisation and quasi-stationarity. Together, these results point to a compound thermodynamic–dynamic anomaly rather than a purely moisture- or dynamics-driven extreme. The proposed framework provides a physically consistent, basin-relevant benchmark for diagnosing exceptional Mediterranean flood-producing precipitation events using high-resolution observations and reanalysis-based process indicators.
How to cite: Espín, D., Benetó, P., and Khodayar, S.: The exceptional October 2024 flooding in Valencia (Spain): meteorological drivers of an extreme precipitation event, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19076, https://doi.org/10.5194/egusphere-egu26-19076, 2026.
Precipitation variability across North Africa spans a wide range of timescales and climatic regimes, from Mediterranean winter precipitation to Saharan convective systems, yet its underlying drivers remain incompletely understood. This contribution synthesizes current knowledge on the atmospheric and surface drivers of precipitation variability in North Africa, drawing on evidence from observations, reanalyses and climate simulations from the Holocene to future projections.
We review the role of large-scale circulation modes, together with synoptic-scale processes such as Rossby wave breaking, cut-off lows, and cyclogenesis, in shaping interannual variability and extreme precipitation events along the Mediterranean coast. Further south, seasonal dynamics linked to the Saharan Heat Low, moisture transport, and land–atmosphere coupling modulate the intermittency and intensity of precipitation in arid regions. Holocene evidence highlights the sensitivity of North African hydroclimate to external forcing and land-surface feedbacks, while also illustrating limits to direct analogy with anthropogenic greenhouse-gas forcing. Future projections indicate that uncertainty in precipitation change is dominated by internal variability and circulation responses, with more robust signals emerging in variability and extremes than in mean precipitation.
As precipitation variability constitutes a climate hazard in its own right, understanding its atmospheric and thermodynamic drivers is central to assessing drought–flood dynamics and their implications for water resources, ecosystems, and human systems across North Africa.
How to cite: Tanarhte, M., De Vries, A.-J., Zittis, G., Armon, M., Hochman, A., Karpasitis, A., Kaskaoutis, D., and Khodayar, S.: Atmospheric drivers and thermodynamic controls of precipitation variability in North Africa, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3580, https://doi.org/10.5194/egusphere-egu26-3580, 2026.
The rising frequency of extreme precipitation is a major concern linked to climate change, commonly associated with increased atmospheric water vapor due to global warming. In densely populated areas, intense rainfall has particularly severe impacts, with urbanization amplifying extreme weather through changes in land surface and local atmospheric conditions. As attribution science increasingly informs climate policy, it is crucial to discern the extent to which shifts in extreme event probability stem from global versus local anthropogenic drivers. This study analyzes multi-decadal daily precipitation records alongside urbanization indices. In line with previous research, results show a general rise in extreme rainfall frequency, with more intense events exhibiting a larger increase. Analysis of population and urban development metrics reveals that the increase is notably smaller in rural areas, suggesting that the rise attributable to local urban development is of the same order of magnitude as that resulting from global warming. This result is shown to be associated with the urban amplification of convective updraft intensification.
How to cite: Guccione, A., Bassi, P., Desbiolles, F., Borgnino, M., D'Andrea, F., and Pasquero, C.: Extreme precipitation changes in relation to urbanization, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7152, https://doi.org/10.5194/egusphere-egu26-7152, 2026.
Atmospheric variability spans interacting regimes set by rotation, stratification, and diabatic forcing. One open question is that diagnosing scale-to-scale energy transfer remains challenging because observations rarely provide complete budget closure. We analyze the June 2019 European heatwave using the Weather Research and Forecasting (WRF) model with a hybrid, scale-adaptive LES closure and five nested domains, resolving horizontal separations from O(102) m to O(106)–O(107) m.
Starting from the governing equations of motion in WRF hybrid vertical coordinate, we derive and appraise generalized two-point, Scale-by-Scale (SbS) budget equations for the second-order moments of horizontal velocity increments, reflecting the kinetic energy at each scale. Whilst equations are written for all scales and any point of the considered domains, their assessment against data is performed in a plane parallel to the ground. SbS energy budget equations account for the inhomogeneity, anisotropy, and all effects present in the first principles. We complement these diagnostics with height-dependent characteristic length scales (Kolmogorov, Taylor, Ozmidov, buoyancy, Rhines and Rossby deformation).
We show results for two cases:
i) In the free troposphere, where the SbS kinetic-energy budget is dominated by the advective term (reflecting non-linear interactions and energy transfer), which is balanced by the pressure-gradient contributions. Radial integration of the advective term reproduces the third-order structure function and exhibits a sign reversal near r ∼ 105 m, reflecting transitions between downscale and upscale kinetic energy transfer across mesoscale–synoptic ranges.
ii) In the lower troposphere, we investigate daytime and nocturnal conditions. First, in daytime conditions, the boundary layer exhibits a classical behavior, in which energy is transferred across scales mainly by advective, non-linear effects. Second, for stable stratification during the night, the pressure contribution increases significantly, and the advective transfer adjusts to the pressure-imposed scale dependence, as already noted in the free atmosphere.
These results provide a physically interpretable framework for diagnosing atmospheric cascades across scales and motivate extending SbS budgets to include thermodynamic variables, such as the moist potential temperature and the water vapor content. The latter would allow us to quantify the contributions of radiative and diabatic forcings over short- and long-term timescales, relevant to climate variability.
How to cite: Sayeed, K., Blervacq, C., Fossa, M., Massei, N., and Danaila, L.: Scale-by-scale two-point statistics in WRF Hybrid LES model, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7744, https://doi.org/10.5194/egusphere-egu26-7744, 2026.
The expected impact of climate change on temperature extremes is an increase in both the frequency and intensity of heat waves, while cold waves are expected to become less frequent and associated with milder cold temperatures. However, cold waves cannot be ruled out, as cold temperatures similar to those experienced in the past can still occur, at least in the near future, albeit with a lower probability.
While many studies have focused on estimating hot extremes in the context of non-stationary climate change, fewer have addressed the estimation of cold extremes, which must be considered for the design of new installations. Unlike hot extremes, which will intensify over time, the coldest values that might affect existing or planned installations are expected to occur now or in the very near future.
Temperature extremes exhibit different types of non-stationarities: a seasonal cycle, the human-induced climate change trend, and interannual to decadal variability. The seasonal cycle is commonly handled by selecting the season prone to the analyzed extremes. Various methods have been proposed to account for the trend due to human-induced climate change in extreme value estimations, either by considering trends in the parameters of statistical extreme value distributions (Coles, 2001; Parey et al., 2007; Gilleland and Katz, 2016; Barbaux et al., 2025, among others) or by computing a reduced variable whose extremes can be considered stationary and then back-transformed (Parey et al., 2013, 2019; Mentachi et al., 2016). However, for cold extremes, interannual variability generally plays a more significant role.
Therefore, in this study, we propose and test an approach to infer extreme cold values representative of the current climate by combining extreme deviations from the average winter mean and variance, as observed during the coldest winters in the past, with the average conditions of current winters. The methodology will first be described then illustrated with examples.
References:
Coles S (2001) An introduction to statistical modelling of extreme values, Springer Series in Statistics. Springer, London
Parey S, Malek F, Laurent C, Dacunha-Castelle D (2007) Trends and climate evolution: statistical approach for very high temperatures in France. Clim Change 81:331–352. https://doi.org/10.1007/s10584-006-9116-4
Gilleland, E., & Katz, R. W. (2016). extRemes 2.0: An Extreme Value Analysis Package in R. Journal of Statistical Software, 72(8), 1–39. https://doi.org/10.18637/jss.v072.i08
Occitane Barbaux, Philippe Naveau, Nathalie Bertrand, Aurélien Ribes, Integrating non-stationarity and uncertainty in design life levels based on climatological time series, Weather and Climate Extremes, Volume 50, 2025,100807, ISSN 2212-0947, https://doi.org/10.1016/j.wace.2025.100807.
Parey S, Hoang TTH, Dacunha-Castelle D (2013) The importance of mean and variance in predicting changes in temperature extremes. J Geophys Res Atmos 118:8285–8296. https://doi.org/10.1002/jgrd.50629
Parey, S., Hoang, T.T.H. & Dacunha-Castelle, D. Future high-temperature extremes and stationarity. Nat Hazards 98, 1115–1134 (2019). https://doi.org/10.1007/s11069-018-3499-1
Mentaschi, L., Vousdoukas, M. I., Voukouvalas, E., Sartini, L., Feyen, L., Besio, G., & Alfieri, L. (2016). The transformed-stationary approach: a generic and simplified methodology for non-stationary extreme value analysis. Hydrology and Earth System Sciences, 20(9), 3527–3547. https://doi.org/10.5194/hess-20-3527-2016
How to cite: Parey, S., Hoang, T. T. H., and Guisnel, B.: How to compute extreme cold levels to design power plants in the climate change context? , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9245, https://doi.org/10.5194/egusphere-egu26-9245, 2026.
Climate change has impacts on natural systems and populations, which can be analysed in attribution studies and attempted to be predicted in forward-looking analyses. Climate extremes in particular can be very impactful, be it in in terms of extreme individual climate hazards, extreme combinations of climate hazards, or less extreme climatic conditions combined with particular settings of exposure and vulnerability resulting in severe impacts. As the field of impact attribution is burgeoning, different perspectives on these complexities become apparent in different study designs, with implications for the research questions they address and the potential role they might play beyond science.
Here, we will give an overview over different climate change impact approaches, including how they each do (or don’t) consider climate extremes. Besides different attribution framings and impact modelling approaches, we will present a discussion of the climate data types typically used in impact attribution, and their implication for capturing impacts of extreme weather and climate. We will especially talk about extreme event attribution framings, and how ‘event’ can be defined in different ways from climate and impact standpoints, respectively. The differences will be illustrated using references to existing literature as well as works in progress, particularly from the field of agriculture-related impacts on food security and nutrition-related health.
How to cite: Undorf, S.: Defining events and extremes in climate change impact attribution, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21133, https://doi.org/10.5194/egusphere-egu26-21133, 2026.
The WASITUS project was established to build towards an operational event attribution capability for Ireland. The project’s aim is to deep dive into the effect climate change has on extreme weather events at a national level, while also providing additional support to international attribution groups such as project collaborators; World Weather Attribution.
By focusing on smaller national scales, and investigating data products used in event attribution, attribution studies can become more accurate and offer deeper insight for local responders and policy makers. A main focus of the WASITUS project is to take advantage of the small geographical size of Ireland and work directly with end-users to better understand how event attribution can help them prepare for future changes in extreme weather. These end-users include members of the public, local representatives, and national policy makers. This directly links attribution with real-world planning and damage mitigation measures.
Focusing on the data side of event attribution, most datasets used, whether reanalysis or models, have been tested at large regional or continental scales. However, we have found that the reanalysis data for Ireland, an island nation on the western boundary of most European datasets, is not as accurate as the data over continental Europe. This is quite possibly the case for other nations globally, where a variety of geographical and observational factors may have led to reanalysis products inaccurately representing the weather and climatology. As Ireland sits on the East of the Atlantic ocean, it is prone to weather threats of marine origin. Therefore, it is important to question the data used in creating the reanalysis and model products for Ireland as changing climate trends impact Ireland in different ways to the rest of Europe.
A particular issue found for reanalysis products is their retrospective extension to earlier decades. To combat this potential issue, we are developing a toolbox to ascertain if reanalysis products reliably characterise the temperatures experienced in a given region for the entirety of the available time-series. The toolbox also aims to identify if shorter subsets of the entire reanalysis timeseries better represent the changing climate than the full dataset. Focusing on ERA5 daily maximum and minimum temperature data over the Republic of Ireland, station observations are being statistically compared to location-specific reanalysis data. While the initial focus will be temperature in Ireland, this toolbox should be readily adaptable for use in different regions globally, as well as on different meteorological parameters, provided sufficient long-term records are available.
In future, it is hoped that other national attribution capabilities, which are being newly formed, can collaborate and aid one another in conducting analysis and report writing. National groups also allow for further research into the methods used for extreme event attribution, where a focus can be placed on improving and expanding the existing attribution capability. In addition, time and focus placed on smaller geographical regions allows for data used in attribution analysis to be thoroughly quality controlled and checked.
How to cite: Bergin, C., Barnes, C., Swan, L., Otto, F., and Thorne, P.: Validation of reanalysis products for extreme event attribution at regional and national levels, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3562, https://doi.org/10.5194/egusphere-egu26-3562, 2026.
Two decades of climate change attribution research have shed light on the impacts of climate change occurring worldwide. The first wave of attribution research quantified climate change impacts on the intensity and probability of extreme weather events and slow-onset changes in glaciers and sea levels. Over the past decade, impact attribution studies have extended these methods to assess the attributable impacts of extreme events on agriculture, health, economic losses and biodiversity. Concurrently, source attribution research quantified individual emitters’ contributions to climate change impacts.
The emissions of individual actors cause climate change impacts. The approximately linear relationship between cumulative CO2 emissions and global temperature rise, combined with the fact that many climate change impacts become progressively worse with rising global temperatures, provides a conceptual basis for this claim. Steady progress towards being able to quantify individual emitters’ contributions to specific losses has brought us closer to true ‘end-to-end’ attribution. However, while studies have quantified emitters’ contributions to aggregate impacts such as regional economic losses, are there circumstances in which we might be able to attribute specific, individual losses to individual actors? This presentation will discuss the scientific possibility of achieving this objective and the legal consequences that may follow.
How to cite: Stuart-Smith, R.: Are we closing in on true ‘end-to-end’ attribution?, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19524, https://doi.org/10.5194/egusphere-egu26-19524, 2026.
The global climate system is undergoing rapid changes unprecedented in human history, with increasingly extreme weather events observed across the world. Antarctica is particularly exposed to these changes, with some of the highest warming rates on the planet recorded over West Antarctica in recent decades and emerging warming trends now evident in East Antarctica. Despite this, relatively few studies have focused on the attribution of extreme temperature events in Antarctica, where near-surface temperatures are strongly conditioned by large-scale atmospheric circulation over the continent and the Southern Ocean.
Here, we apply a circulation-analogue technique for extreme-event attribution to assess how dynamically similar warm extremes have changed over time. We focus on three recent austral-summer warm extremes: the February 2020 heatwave over the Antarctic Peninsula, the March 2022 warm anomaly across East Antarctica, and the March 2015 warm spell on the Peninsula. These short-duration events produced exceptional near-surface temperature anomalies.
Circulation analogues associated with these events are analysed across two climatic periods: a “past’’ baseline (1948–1986) and a “present’’ period (1987–2025), using two independently developed atmospheric reanalysis products, ERA5 and JRA-3Q. Changes in the occurrence frequency of analogue weather types and in their associated near-surface temperature anomalies provide insight into the influence of anthropogenic climate change on these extremes. The dual-dataset approach offers a more robust basis for attribution, particularly for the pre-satellite era when reanalysis uncertainties and dataset discrepancies are considerable.
How to cite: Ichikawa, Y., S. Fuckar, N., Bracegirdle, T., and Ginesta, M.: Attribution of Austral Summer Extreme Temperature Events in Antarctica Using a Circulation Analogue Method , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18062, https://doi.org/10.5194/egusphere-egu26-18062, 2026.
The risk of extreme climate events is increasing due to the compounding effects of climate change and the increasing dependence on natural resources, with impacts that cascade through ecosystems, livelihoods, and institutions long after the event itself. Climate services are therefore increasingly central to adaptation, providing information that helps anticipate hazards, guide preparedness, and support response. Yet, adaptation can often turn maladaptive when it unintentionally shifts risk to other groups, degrades ecological buffers, or locks systems into trajectories that increase their long-term vulnerability. Climate services rarely account for these unintended consequences, despite their centrality in what decisions can be taken and by whom. Against this backdrop, our contribution presents a methodological framework that integrates system thinking and system dynamics modelling to anticipate how climate services shape long-term socio-ecological outcomes of climate extremes, including the risk of maladaptation.
Our framework combines four elements. First, we use system archetypes to identify recurring maladaptive patterns relevant to extremes’ impacts, such as risk shifting across space or social groups, and “fixes” that reduce immediate losses while degrading ecological resilience. Second, these dynamics are refined through a stakeholder-led iterative process. Third, maladaptation risk and adaptation trade-offs are evaluated and described. Fourth, these dynamics are formalized in a system dynamics model to test different climate information scenarios.
Our application of this framework shows that different typologies of climate services can influence long-term impact trajectories by influencing what risks are prioritized, which measures are selected, and who is able to act. Additionally, under increasing climate variability and compounding shocks, these dynamics become more pronounced, increasing the likelihood that short-term coping undermines long-term resilience. Consequently, accessible and long-term climate services become pivotal in ensuring sustainable adaptive strategies benefitting all stakeholders.
By linking climate services to the complex, socio-ecological impact of climate extremes, this approach lays the groundwork for testing the risk of maladaptation in the development of climate services and adaptation strategies, supporting equitable and durable disaster impact reductions.
How to cite: Biella, R., Brandimarte, L., Mazzoleni, M., and Di Baldassarre, G.: Understanding Complexity to Anticipate Maladaptation: A System Dynamics Approach to Climate Extremes Adaptation with Climate Services, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11777, https://doi.org/10.5194/egusphere-egu26-11777, 2026.
Climate change adaptation (CCA) is supported by a rapidly expanding ecosystem of decision-support systems, risk and vulnerability assessments, data portals, guidance frameworks, and early-warning services. Yet selecting an appropriate tool for a specific decision context remains difficult because tool information is often fragmented, inconsistently described, and not searchable using the metadata that practitioners actually need (e.g., sector, scale, user group, methods, outputs, usability, cost, and geographic scope). Within the FutureMed COST Action, WG2 has compiled a structured inventory of Mediterranean-relevant CCA tools and developed a shared criteria systematization to describe who tools are intended to serve, what they support, and how they are applied in practice. Insights emerging from this collaborative effort highlight that availability is not the only challenge: tool–context alignment is frequently unclear, tools often operate in isolation with limited guidance for selection, and the way tools define their spatial applicability may follow administrative rather than physical boundaries. Multilingual support and pathways for incorporating local data and knowledge are uneven. These patterns motivate the need for an operational resource that makes tools legible, comparable, and easier to navigate for real-world use.
We present ADAPT-TOOLS, a live database and web platform that translates a fragmented inventory into actionable discovery through structured metadata and faceted exploration. Tools are organized using a harmonized taxonomy spanning several aspects: intended user groups (policy, local government, private sector, NGOs, academia), sector focus, tool type, political and physical target scales, temporal horizon and resolution, methodological approach, data utilization, output types, accessibility/usability, validation and reliability signals, cost and support characteristics, and geographic applicability. Users can combine filters (OR within filters, AND across filters) to rapidly narrow from broad categories to tools matching their constraints, while dedicated tool pages support transparent comparison and adoption.
Technically, the platform is implemented as a containerized stack with a relational backend and a web interface. A reproducible ingestion pipeline converts structured inventories into relational tables, enabling systematic updates and maintainable curation workflows. To support sustained evolution and community engagement, ADAPT-TOOLS includes a moderated “Suggest a Tool” workflow that collects structured submissions for review before integration, enabling continuous expansion while preserving data quality. The platform is publicly deployed at adapt-tools.org. By linking community mapping to an operational platform, ADAPT-TOOLS supports evidence-informed and more context-aware adaptation planning across the Mediterranean and beyond.
Acknowledgments
This study is based on work from COST Action CA22162 “FutureMed: A Transdisciplinary Network to Bridge Climate Science and Impacts on Society” (FutureMed), supported by COST (European Cooperation in Science and Technology).
How to cite: Tsilimigkras, A., Pagé, C., Tošić, M., Lazić, I., Savelli, E., and Koutroulis, A. and the FutureMed WG2: From Mapping to Action: ADAPT-TOOLS and What We Learn from the Mediterranean CCA Toolscape, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14429, https://doi.org/10.5194/egusphere-egu26-14429, 2026.
Earth Observation for high-impact multi-hazard science (EO4Multihazards) was a European Space Agency (ESA) project that developed methodologies for risk (hazard, vulnerability, exposure) and impact assessment with the help of Earth Observation (EO) data. We assessed cascading and compound events and developed impact chains for four case studies in Italy (upper and lower Adige river basin), the United Kingdom and Dominica, a Caribbean Small Island Developing State. This abstract presents the fifth, so-called “transferability”, case study, where developed methodologies were applied in an area with limited ground validation data, Senegal. Droughts, heatwaves, floods and fires were analysed for the regions specified by stakeholders. The risk for the population and the impact on agricultural yields were assessed in the riskchanges.org platform. The vulnerability components were shown to be the most challenging and ground-data demanding. Visit our website to explore other outputs, such as a whole Europe event database and case study geostories https://eo4multihazards.gmv.com/.
We acknowledge support from the EO4Multihazards project (Earth Observation for high-impact multi-hazards science), contract number 4000141754/23/I-DT, funded by the European Space Agency and launched as part of the joint ESA-European Commission Earth System Science Initiative.
How to cite: Prikaziuk, E., Furlanetto, J., van den Bout, B., Boscarin, G., Huesca, M., Albergo, E., Masina, M., Mauro Ferrario, D., Maraschini, M., Torresan, S., van Westen, C., Manzella, I., and Domenech, C.: EO4Multihazards: Earth Observation for high-impact multi-hazard science, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14636, https://doi.org/10.5194/egusphere-egu26-14636, 2026.
Attribution science has made substantial progress in quantifying the influence of anthropogenic climate change on extreme events, yet its application to human health outcomes remains limited and difficult to operationalize for health-sector practitioners. Methodological complexity, fragmented guidance, and challenges in interpreting and communicating results hinder the uptake of climate-health attribution evidence in public health decision-making. We present the development of a structured, accessible resource designed to support health-sector engagement with climate-health attribution and its application in public health decision-making, within the TACTIC (HealTh ImpAct ToolkIt for Climate change attribution) project funded by the Wellcome Trust. This work is designed as an accessible, practice-oriented resource that complements technical methodological materials, supporting users who wish to understand or engage with climate-health attribution studies. While primarily targeting public health professionals and health agencies, it is also intended to be useful for researchers, policy advisors, and communicators working at the climate-health interface. This work synthesizes existing evidence and emerging best practices in health impact attribution and is structured around key practical questions: when attribution is feasible for specific climate hazards and health outcomes; what data, assumptions, and methods are required; how results should be interpreted and communicated; and how uncertainty and limitations should be conveyed. Its development is informed by stakeholder engagement, community input, and applied case studies in climate-vulnerable regions, ensuring relevance across diverse geographical and resource contexts. By translating complex attribution concepts into clear, actionable guidance, this work aims to build capacity, support evidence-informed public health action, and strengthen the integration of climate-health attribution science into policy and practice.
How to cite: Corpuz, B., Ryan, S., Stuart-Smith, R., Santos Vega, M., Carrasco-Escobar, G., Marrufo, T., Chirombo, J., Shumake-Guillemot, J., Vicedo-Cabrera, A., and Lowe, R.: Bridging Climate-Health Attribution Science and Health-Sector Practice, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15294, https://doi.org/10.5194/egusphere-egu26-15294, 2026.
Human-induced climate change has increased heat stress, leading to significant losses in work productivity and subsequent economic repercussions. Not only are the climate change-related losses in work productivity due to heat unequally distributed around the globe, but the contributions of individual nations to these losses through greenhouse gas emissions are also disproportionate. Here, we present a source attribution approach that links historical national emissions to global lost working hours resulting from increased heat exposure.
Following the framework of Callahan & Mankin (2022 & 2025), we conduct the source attribution study in three steps: First, we calculate the contribution of past national emissions to the change in global mean surface temperature (GMST) using the reduced-complexity climate model Finite amplitude Impulse Response (FaIR). Second, we apply a pattern scaling technique, trained on outputs from general circulation models, to translate GMST changes into grid-level heat stress metrics, here the wet bulb globe temperature (WBGT). Third, we use the simulated GMST changes due to national emissions, the pattern scaling coefficients, and two literature-based exposure-response functions to estimate the potential loss of working hours attributable to national emissions at grid level. By integrating demographic data on population and employment, we derive estimates of total potential losses in working hours linked to specific nations' emissions. Additionally, we thoroughly assess uncertainties arising from global climate models, the FaIR model, and the exposure-response functions.
Our preliminary results highlight the different responsibilities of nations for the costs associated with increased occupational heat stress. The study thereby contributes to the growing body of literature linking individual emitters with experienced harms, providing critical insight into climate liability and national accountability for climate policy.
Callahan, C. W., & Mankin, J. S. (2022). National attribution of historical climate damages. Climatic Change, 172(3–4), 1–19. https://doi.org/10.1007/S10584-022-03387-Y/FIGURES/4
Callahan, C. W., & Mankin, J. S. (2025). Carbon majors and the scientific case for climate liability. Nature 2025 640:8060, 640(8060), 893–901. https://doi.org/10.1038/s41586-025-08751-3
How to cite: Romanovska, P., New, M., Gornott, C., Brouillet, A., and Undorf, S.: Source attribution: From national emissions to global loss in working hours due to climate-change increased heat, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21503, https://doi.org/10.5194/egusphere-egu26-21503, 2026.
The Mediterranean is a climatologically sensitive region due to its transitional position between the arid subtropics and the wetter mid-latitudes. In recent years, Mediterranean tropical-like cyclones, or Medicanes, have gained increasing attention. These rare baroclinic cyclones that evolve in their mature stage into vortices with structural characteristics similar to tropical cyclones. Although they occur only a few times per decade, Medicanes can produce severe socio-economic impacts through intense precipitation, strong winds, and coastal flooding.
Observational and modeling studies indicate that rising sea surface temperatures may affect Medicane evolution, potentially leading to stronger storms. Understanding their dynamics is therefore important not only for climatology but also for operational sectors such as aviation, which are directly exposed to atmospheric hazards. While the surface impacts of Medicanes have been widely studied, their influence on upper-tropospheric conditions, particularly turbulence relevant to aviation, remains poorly documented. In-flight encounters with turbulent eddies represent a major aviation hazard, often resulting in injuries, aircraft damage, and economic losses to airlines.
This study presents the first systematic investigation of aviation-scale turbulence associated with eleven Medicanes that occurred between 1996 and 2023. The analysis is based on three empirical turbulence diagnostics (TI1, TI2, and TI3), commonly used to identify synoptic-scale patterns conducive to shear-induced turbulence. These indices, derived from the ERA5 reanalysis dataset, are computed for each Medicane across the 900–200 hPa layer and as a function of radial distance from the cyclone center, with the aim of assessing how turbulence conditions within Medicanes evolve in a changing climate.
How to cite: Simone, M., Servidio, S., Miglietta, M. M., and Alberti, T.: Characterization of aviation turbulence associated with Mediterranean tropical-like cyclones (Medicanes), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12488, https://doi.org/10.5194/egusphere-egu26-12488, 2026.
Posters on site: Thu, 7 May, 08:30–10:15 | Hall X4
On 3 May 2025, a severe hailstorm affected Paris and parts of western Europe. We assess whether anthropogenic climate change contributed to its intensity using ERA5 reanalyses and an analogue-based attribution framework. The synoptic pattern featured a cut-off low and a surface cold front following several warmer-than-normal days. We identify circulation analogues to 3 May 2025 in two periods, namely a cooler “past” (1974–1999) and a warmer “present” (1999–2024). We then compare thermodynamic conditions under otherwise similar large-scale flow. Hail probability and size are estimated with two models: (i) a logistic formulation using Convective Available Potential Energy (CAPE), deep-layer wind shear, and convective precipitation, and (ii) an extended model including freezing-level height and 850 hPa temperature, tailored to European hail environments. Models are calibrated with ˆIle-de-France observations and validated independently. Present-day analogues exhibit significantly higher CAPE, a higher freezing level, and similar deep-layer shear, yielding larger hail probability and size. These results indicate that human-induced warming likely enhanced the hailstorm severity in this synoptic setting.
How to cite: Faranda, D. and Alberti, T.: Investigating the Role of Climate Change in the 3 May 2025 Western Europe Hailstorm Using Atmospheric Analogues, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2862, https://doi.org/10.5194/egusphere-egu26-2862, 2026.
Thunderstorm activity and associated turbulence pose significant operational challenges for major airports, especially in the context of a changing climate. This study analyzes a high impact winter convective event that forced delays and cancellations at the Rome-Fiumicino airport. We investigate how the synoptic conditions of similar events have evolved over the past five decades (1974–2024) using reanalysis data and a pattern analog approach. We compare atmospheric configurations from the past (1974-1999) and recent (1999-2024), focusing on key parameters related to convection and turbulence. For similar synoptic configurations, our results show an increase in Convective Available Potential Energy (up to 20%), low-level vertical wind shear (up to 20–25%), and turbulence (up to 25-30 %) near Rome-Fiumicino airport in the more recent period, indicating a greater potential for organized convection and turbulence. The analysis of vertical atmospheric profiles reveals enhanced wind shear and turbulence especially in the lower troposphere (0-3 km), with implications for mechanical turbulence during aircraft approach and departure. At Rome-Fiumicino airport, the number of fog and thunderstorms during similar synoptic patterns is increased (from 1 to 4), average approaching visibility decreased from 10 to 7 km, stronger surface winds (from 10 to 15 km/h) are observed, with also increases in average temperatures (from 11 to 13 °C). Finally, using a multinomial logistic model we show that hazardous weather events, particularly thunderstorms and hail, are becoming more frequent for similar recent events (from 2% to 6% annual occurrence). These trends are linked to both human-driven climate change and long-term variations in large-scale modes of natural variability.
How to cite: Alberti, T. and Faranda, D.: Was the 13 December 2024 severe thunderstorm over Rome-Fiumicino airport intensified by climate change?, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2952, https://doi.org/10.5194/egusphere-egu26-2952, 2026.
How to cite: Sparrow, S., Perez-Fernandez, I., and Tett, S.: Attribution study of the 2023-2024 Drought on the South of Africa., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-23150, https://doi.org/10.5194/egusphere-egu26-23150, 2026.
The Mediterranean region is widely recognized as a climate change hotspot, as anthropogenic warming is projected to substantially increase air temperatures by the end of the 21st century, together with longer periods of reduced rainfall. The region is likely to experience warmer and drier conditions with significant consequences for human societies, while the intensification of heatwaves is likely to trigger cascading hazards. At the same time, heavy precipitation events during hot periods may become more common, increasing the likelihood of urban flash floods, especially in densely populated metropolitan areas.
Instead of focusing only on single climate extremes,, compound extremes offer a complementary perspective for assessing future climate risks. We analyze two compound climate indices: Warm/Dry (WD) and Warm/Wet (WW) days. The analysis focuses on representative Mediterranean metropolitan areas characterized by high population density and climatic relevance.
The indices are derived from daily mean temperature and precipitation data obtained from an ensemble of CMIP6 climate model simulations. Annual and seasonal frequencies of compound extremes are evaluated for the mid-century (2041–2060) and late-century (2081–2100) periods, relative to a 1995–2014 reference period, under the SSP2-4.5 and SSP5-8.5 scenarios. Results indicate a robust increase in the frequency of Warm/Dry days across all future scenarios, suggesting that Mediterranean climates will increasingly experience concurrent warming and drying. In contrast, Warm/Wet days are scenario-dependent. These findings highlight a dual climate risk for Mediterranean cities, where more frequent prolonged hot and dry conditions coexist with a higher chance of compound heat and heavy precipitation events under high-emission scenarios.
How to cite: Polychroni, I., Hatzaki, M., Patlakas, P., and Nastos, P.: Future Warm–Dry and Warm–Wet Compound Climate Extremes in Mediterranean Metropolitan Areas under Climate Change, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18974, https://doi.org/10.5194/egusphere-egu26-18974, 2026.
Climate change is changing the statistics and the physics of extreme weather events, leading to increasing impacts from heavy precipitation, floods, droughts, heatwaves, and so on. Thus, attribution of extremes requires a process-based understanding of how large-scale forcing interacts with regional dynamics and thermodynamics. Despite significant progress at global scales, attribution of extremes at regional and local scales remains challenging, particularly in regions where small-scale processes dominate the generation of high-impact events.
The Mediterranean basin is a hotspot for climate change, characterized by land–sea interactions, complex orography, and convective activity. Extreme events in this region are often controlled by small-scale (1–10 km) processes, including atmospheric instability and convective organization. These processes are poorly represented in coarse-resolution climate models, limiting our ability to attribute observed impacts and to assess future risks.
The Mediterranean Extreme Events and Tipping elements in a changing climate on multiple spatiotemporal scales (MEET) project addresses this challenge through a process-oriented, high-resolution framework focused on Mediterranean extremes and their impacts. MEET will identify and classify historical and recent extreme events based on their impacts on key meteorological variables, such as precipitation intensity, near-surface temperature extremes, and damaging winds, and on associated societal and environmental consequences. Physics-informed decomposition techniques combined with advanced statistical methods will be applied to identify analog events across multiple spatiotemporal scales, enabling the detection of changes in event frequency, intensity, and spatial structure. A central component of MEET is the use of convection-permitting climate simulations to explicitly resolve the small-scale dynamics and thermodynamics underlying extreme events in both past and future climates. By linking high-resolution physical processes to observed impacts, MEET aims to advance the attribution of Mediterranean extreme events and to provide a physically consistent basis for improved regional risk assessment under ongoing climate change.
Acknowledgements
This research has been carried out with funding from the Italian Ministry of University and Research under the FIS-2 Call.
How to cite: Alberti, T., de Leeuw, J., Scardino, G., Siciliano, F., and Zazulie, N.: Mediterranean Extreme Events in a changing climate on multiple spatiotemporal scales, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17367, https://doi.org/10.5194/egusphere-egu26-17367, 2026.
Extreme flood events are among the most damaging climate-related hazards, with significant human and socio-economic impacts. Understanding the extent to which anthropogenic climate change influences both the physical characteristics and impacts of such events is important for supporting policymakers in risk management and adaptation, informing loss and damage mechanisms, and raising public awareness of the impacts of climate change. Here, we apply a circulation-analogue attribution approach to quantify the impacts of climate change on flooding, extending the use of dynamical analogues from hazard attribution to impact analysis. The framework is designed to work with limited data, making it particularly relevant for data-scarce regions, including much of the Global South.
In late April and early May 2024, extreme flooding affected large parts of the state of Rio Grande do Sul in southern Brazil, being the largest floods ever observed along several regional rivers. The event caused at least 183 fatalities and affected more than 2.3 million people, making it one of the most severe climate-related disasters in Brazil’s history. Weekly rainfall totals exceeded 300 mm across much of the state and 500 mm locally.
In this study, we assess the influence of anthropogenic climate change on the socio-economic impacts of this extreme flood event using a three-step attribution framework. First, we attribute the total event rainfall to climate change by identifying dynamical analogues—events with similar large-scale atmospheric circulation—in single-model initial-condition large ensembles under factual and counterfactual climate conditions. Second, the resulting precipitation signals are used to force a hydrological flood model to quantify climate-induced changes in flood magnitude and spatial extent. Finally, we evaluate the associated socio-economic impacts based on the climate-attributed flood signal.
How to cite: Ginesta, M., Laipelt, L., Franta, B., and Stuart-Smith, R. F.: Attribution of the Impacts of the 2024 Extreme Floods in Rio Grande do Sul, Brazil, to Climate Change , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12606, https://doi.org/10.5194/egusphere-egu26-12606, 2026.
It is the combination of internally induced oscillations and externally forced climate change signals that we observe and feel every day as climate conditions. External forcing can change not only the mean state, but also the internal variability. One of the most important and impactful aspects of variability is the frequency and magnitude of extremes. Even though the cold extremes are expected to warm, they can still have severe impacts on society and ecosystems, which have adapted to a warmer climate. We investigate how the internal variability of winter temperature might change under stronger radiative forcing. For this purpose, we utilize two different datasets: a set of LongRunMIP simulations, analyzing near-equilibrium conditions under preindustrial and abrupt 4xCO2 forcings, and transient large ensemble simulations comparing the historical and scenario periods (the end of the 21st century under RCP8.5/SSP5-8.5 socio-economic pathways). We focus on northern middle latitudes (40 – 70 ° of latitude). In this region, the near-surface climate is largely influenced by atmospheric circulation, including various large-scale modes of variability. A change in the shape of the temperature distribution can then point to a fundamental change in climate-governing processes. It has been argued that increasing winter mean temperatures would be accompanied by a decrease in variance, as day-to-day temperature variations are induced by the occurrence of synoptic-scale weather systems, and in warmer climates, this is expected to decline. Our study provides new insights, showing that the variance shrinking is spatially heterogeneous. We further concentrate on the skewness of the temperature distribution and investigate the changes in the lengths of the cold and hot tails, which are related to the changes in variance. In many mid-latitude regions, the skewness is decreasing, and the cold tail is shrinking at a slower rate than the hot tail, implying enduring cold extremes, even in climatic states much warmer than those we are familiar with.
How to cite: Holtanova, E., Van Loon, S., and Rugenstein, M.: Cold extremes enduring in a much warmer world, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9126, https://doi.org/10.5194/egusphere-egu26-9126, 2026.
Sudden Stratospheric Warmings (SSWs) are extreme atmospheric events characterized by a rapid weakening or breakdown of the polar vortex, often followed by profound impacts on surface weather. These include abrupt temperature anomalies, shifts in large-scale circulation patterns, modulation of jet streams, and an increased likelihood of cold-air outbreaks and altered storm tracks at mid-latitudes. As a result, SSWs play a pivotal role in shaping the occurrence and intensity of extreme weather events across the Northern Hemisphere. Although low-dimensional models have proven instrumental in elucidating the fundamental wave–mean flow interactions underlying SSWs, their ability to faithfully reproduce the full complexity, variability, and predictability of real atmospheric dynamics remains limited.
In this study, developed within the framework of the VORTEX project, we introduce a novel data-driven methodology to systematically assess the realism and predictive skill of low-dimensional models in simulating SSW dynamics. Our approach is based on two complementary metrics, dimension and persistence, which quantify, respectively, the effective dynamical complexity and the temporal coherence of the system. Together, these metrics provide a robust framework to evaluate how well simplified models capture the essential features of observed stratospheric variability.
Using this methodology, we investigate the sensitivity of SSW dynamics to large-scale tropospheric forcing and stochastic variability, both of which are known to be key contributors to vortex destabilization. To this end, we propose a stochastic low-order model that couples the Holton–Mass equations, representing wave–mean flow interactions, with a Langevin formulation that accounts for the bistable nature of the polar vortex.
Our results demonstrate that both the frequency and dynamical characteristics of SSWs exhibit a pronounced sensitivity to changes in tropospheric wave forcing and noise intensity. We identify critical thresholds beyond which the probability of vortex breakdown increases sharply, offering a mechanistic interpretation of the observed intermittency and variability of SSW events. These findings provide new insight into stratosphere–troposphere coupling and highlight the potential of data-driven diagnostics to bridge the gap between conceptual models and the complexity of the real atmosphere.
How to cite: Alvarez-Castro, C., Peña-Ortiz, C., Gallego, D., and Faranda, D.: Exploring Sudden Stratospheric Warming Dynamics: A Data-Driven Analysis Using a Low-Dimensional Stochastic Model, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14907, https://doi.org/10.5194/egusphere-egu26-14907, 2026.
Heatwaves are among the most impactful and rapidly intensifying climate extremes in the Mediterranean region, where rising mean temperatures and the increasing frequency of extreme events interact with urban environments, exacerbating thermal stress. In densely populated cities, the Urban Heat Island (UHI) effect acts as a local amplification mechanism, transforming large-scale atmospheric heatwaves into compound extreme events with significant societal and environmental consequences. This study analyzes the spatial distribution and main controlling factors of extreme surface temperatures during three intense summer heatwaves in Thessaloniki, Greece, with the aim of linking observed geophysical extremes to urban configuration and assessing the potential of mitigation measures. For this aim, we employ LANDSAT 8–9 satellite imagery processed in QGIS to derive high spatial resolution Land Surface Temperature (LST) fields, together with key land-cover indicators such as the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Built-up Index (NDBI). These remote-sensing products are integrated with urban morphology and land-use data derived from OpenStreetMap (OSM), enabling a detailed characterization of how vegetation cover, building density, and surface materials modulate the urban thermal response under conditions of extreme atmospheric forcing. The results reveal pronounced spatial heterogeneity in LST across the metropolitan area, with persistent hotspots associated with compact historic districts, industrial zones, and highly impervious surfaces. In contrast, urban parks, coastal areas, and neighborhoods with a higher fraction of vegetation exhibit significantly lower surface temperatures, highlighting the role of land–atmosphere interactions and surface energy balance feedbacks in shaping urban-scale thermal extremes. The inverse relationship between NDVI and LST, together with the positive relationship between NDBI and LST, indicates the strong sensitivity of urban surface temperatures to land-cover composition during heatwave conditions. By framing the UHI as an intrinsic component of compound heat extremes, this work bridges observational geophysical analysis with the assessment of urban impacts. We further explore the potential of targeted mitigation strategies, such as the large-scale implementation of green roofs and high-albedo pavements, demonstrating their ability to reduce extreme surface temperatures and to moderate thermal exposure. The findings emphasize the importance of integrating physically grounded, data-driven mitigation measures into standardized urban planning frameworks in order to enhance resilience to future thermal extremes. More broadly, the study contributes to the understanding of how local-scale processes interact with large-scale climate extremes, offering transferable insights for Mediterranean and European cities increasingly exposed to heatwave risk under climate change.
How to cite: Falda, M., Adamos, G., Radenovic, T., and Laspidou, C.: Satellite-Based Analysis of Urban Heat Island Dynamics under Extreme Heatwave Conditions and Mitigation Strategies in Thessaloniki, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17874, https://doi.org/10.5194/egusphere-egu26-17874, 2026.
The analysis of the impacts due to climate extremes, such as extreme precipitation, heatwaves, and tropical cyclones, needs to rely on multimodal data, ranging from complex geophysical fields to textual and visual data.
While recent advances in vision-language models (VLMs) have stimulated interest in multimodal-driven climate analysis, their application to natural hazard analysis is still relatively limited.
In this work, we focus on tropical cyclones, and construct a new framework, namely Visual Object Representation for Tropical Cyclone Extremes and eXtent (VORTEX), a physics-aware, visual abstraction designed to support interpretable vision-language reasoning over hazard fields for tropical cyclones.
VORTEX transforms spatiotemporal reanalysis data associated to tropical cyclones into structured, visually identifiable representations by explicitly encoding cyclone-specific physical properties, including pressure-anchored storm geometry, wind and precipitation intensity extrema, spatial asymmetry, and field-scale footprint.
Building on VORTEX, we construct ClimateFieldQA, a structured evaluation framework for diagnosing VLM reasoning over tropical cyclone hazard fields. ClimateFieldQA comprises 4,978 high-resolution reanalysis heatmaps and 243,922 instruction samples spanning spatial localization, intensity estimation, structural pattern recognition, field-scale extent reasoning, and physical impact analysis.
ClimateFieldQA is designed to expose strengths, limitations, and failure modes of VLM-based reasoning under physically constrained geoscientific settings.
Using ClimateFieldQA, we show that physics-aware visual abstractions systematically improve structure-sensitive reasoning and reduce common interpretation errors observed when VLMs operate on raw hazard fields, highlighting the methodological importance of representation design for climate impact analysis and natural hazard assessment in Earth system science.
How to cite: Xiao, L. and Mengaldo, G.: ClimateFieldQA: Evaluating Vision–Language Models on Tropical Cyclone Hazard Fields with Physics-Aware Visual Abstractions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18916, https://doi.org/10.5194/egusphere-egu26-18916, 2026.
Posters virtual: Thu, 7 May, 14:00–18:00 | vPoster spot 1b
EGU26-21173 | Posters virtual | VPS23
Global Hot Spots of Climate Extremes from Composite Hazard IndicesThu, 07 May, 14:03–14:06 (CEST) vPoster spot 1b
Understanding the spatial distribution and intensity of climate-related hazards is essential for effective risk assessment and adaptation planning. This study presents a comprehensive analysis of climate hazard indices applied across all IPCC reference regions, using all the available CMIP5-driven regional climate model (RCM) simulations at 25 km resolution over the CORDEX domains, together with Euro-CORDEX simulations at 12 km resolution. The objective is to identify climate hazard hot spots through the formulation of a composite hazard index.
A subset of hazard indicators representing key climate extremes is selected. Temperature- and heat-stress–related hazards are characterized using TX90p (extreme maximum temperature), TN90p (extreme minimum temperature), and the NOAA Extended Heat Index (HI). Heavy precipitation and drought-related hazards are represented by RX1DAY (maximum 1-day precipitation), P99 (99th percentile of precipitation), and CDD (consecutive dry days).
The composite index integrates both the frequency and intensity of extremes and is computed at both regional and grid-point levels. A normalization approach is used to ensure comparability across regions with diverse climatic characteristics. Results reveal pronounced spatial heterogeneity in hazard intensity, highlighting regions where multiple hazards converge and amplify overall risk. This framework enables systematic identification of global and regional climate hot spots, offering insights into areas that may face heightened climate stress under current and projected conditions. By providing a consistent, region-wide assessment of hazard exposure, this study aims to support comparative climate risk analyses and inform policy-relevant decision-making for climate adaptation and resilience strategies at multiple scales.
How to cite: Zazulie, N., Raffaele, F., and Coppola, E.: Global Hot Spots of Climate Extremes from Composite Hazard Indices, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21173, https://doi.org/10.5194/egusphere-egu26-21173, 2026.
