The research team, led by Ehud Bartfeld and Dr. Assaf Hochman from the Hebrew University of Jerusalem, in collaboration with Dr. Alexandre M. Ramos from the Karlsruhe Institute of Technology, embarked on an in-depth investigation into Heavy Precipitation Events (HPE) in the western Iberian Peninsula. These extreme precipitation episodes have recently been linked with growing risks to urban infrastructure, water management systems, and overall public safety amid a shifting climate paradigm that intensifies hydrological extremes.

Central to their findings is the pivotal role of atmospheric rivers, which are long, narrow bands of concentrated water vapor that traverse oceans and transport vast quantities of moisture into coastal regions. The study identified that storms involving atmospheric rivers produce markedly heavier rainfall — approximately 36% more intense on average than events without such moisture conveyor belts. This increase in precipitation intensity does not simply arise from an overall elevation in atmospheric moisture content. Instead, it is fundamentally driven by amplified low-level winds that channel moisture more efficiently into affected regions, thereby enhancing rainfall delivery to the surface.

In the words of the researchers, “It’s not just how much water the atmosphere holds. It’s how effectively the system delivers that water to the ground.” This distinction underscores a nuanced understanding of precipitation dynamics: it’s the meteorological mechanisms organizing moisture transport and convergence that govern extreme rain events, not solely the atmospheric moisture budget.

One of the most challenging questions the study addresses is the intrinsic predictability of these extreme rainfall occurrences. Utilizing a novel dynamical systems approach, the researchers meticulously analyzed the evolution of atmospheric patterns before and during heavy precipitation episodes. This method involves examining both the lower and upper atmospheric layers to capture the full spectrum of dynamic interactions governing storm development and progression.

Their analysis uncovered a remarkable bifurcation in predictability. The most intense and destructive rainfall events are not random anomalies but are consistently linked with well-organized, deep extra-tropical cyclones forming over the North Atlantic, near 50°N latitude and 15°W longitude. These cyclonic systems are characterized by pressure anomalies nearly double the magnitude of those seen in less predictable storms, clearer jet stream interactions, and more coherent large-scale atmospheric wave patterns.

The practical implications of this finding are profound. The highly predictable storms exhibited rainfall intensities approximately 80% greater than their less organized counterparts, making them both exceptionally dangerous and notably “readable” from a forecast perspective. This revelation defies the common perception that the severest storms are the most capricious, revealing instead that strong atmospheric signals can precede the most hazardous events.

The December 2022 storm that ravaged western Portugal served as a pivotal case study illustrating this phenomenon. This particular event featured an atmospheric river that aligned synchronously with a powerful extratropical cyclone and a well-defined jet stream configuration. This confluence resulted not only in prodigious rainfall and widespread flooding but also in relatively high forecast confidence leading up to the storm. Such alignment can provide vital lead time for preparations and emergency responses if the atmospheric signals are correctly interpreted and communicated.

Integrating atmospheric river detection with dynamical systems analysis presents a promising frontier in meteorological research. By combining these methodologies, forecasters could enhance their ability to pinpoint the timing and magnitude of heavy precipitation events with unprecedented accuracy. Such advances could extend beyond the Iberian Peninsula, benefiting any coastal regions prone to moisture-driven storms, including parts of North America, Asia, and Oceania.

The study also carries broader implications in the context of a changing climate. As anthropogenic warming intensifies the hydrological cycle, extreme rainfall events are expected to increase both in frequency and severity. Distinguishing between chaotic atmospheric noise and organized, predictable patterns becomes critical for improving resilience and adaptive planning. This research highlights that the atmosphere occasionally broadcasts clear, coherent signals of extreme weather—signals which humanity can learn to read more effectively.

From a scientific perspective, these findings challenge meteorologists to reconsider traditional forecasting paradigms that have often regarded extreme events as irreducibly uncertain. By applying advanced frameworks from dynamical systems theory, the atmospheric community can better understand and anticipate the nonlinear interactions that precipitate heavy rainstorms. This could revolutionize predictive capabilities, converting the chaos of climate extremes into more manageable and forecastable phenomena.

The implications extend as well to infrastructure design and emergency management. Knowing in advance that a forecasted event is both intense and intrinsically predictable enables more targeted preparations, reducing economic losses and saving lives. Furthermore, as researchers decode the atmospheric signatures that precede these storms, they open new avenues for improving numerical weather prediction models, which are the cornerstone of operational forecasting worldwide.

In conclusion, this study marks a significant leap in meteorological science by unveiling the hidden predictability of some of the most intense storms impacting Portugal and similar regions. As climate change continues to reshape weather patterns globally, unlocking the secrets of atmospheric predictability will be essential in safeguarding vulnerable communities. The atmospheric rivers and cyclonic systems previously thought to produce chaotic havoc may, paradoxically, offer some of the clearest windows into the future of extreme weather forecasting.

Subject of Research: Not applicable
Article Title: Intrinsic predictability of heavy precipitation influenced by atmospheric rivers in the Western Iberian Peninsula
News Publication Date: 11-Apr-2026
Web References: DOI 10.1016/j.wace.2026.100895
Keywords: Weather, Precipitation, Dynamical systems, Climatology

Supercell thunderstorms represent some of the most intense and destructive weather phenomena in Europe, carrying the potential for devastating impacts on human lives, infrastructure, and the environment. Defined by their unique rotating updrafts of warm, moist air, these storms are notorious for producing severe weather conditions, including violent winds, large hailstones, and torrential rainfall. Unlike ordinary thunderstorms, supercells sustain a persistent mesocyclone—a deep, rotating updraft—enabling these systems to develop with exceptional longevity and intensity. Across Europe, they largely manifest during the summer months, but understanding their current behavior and future evolution has proven challenging due to limitations in observational and modeling techniques.

A landmark collaboration between the University of Bern’s Institute of Geography, the Oeschger Center for Climate Change Research, the Mobiliar Lab for Natural Risks, and ETH Zurich’s Institute for Atmospheric and Climate Science has culminated in the first high-resolution simulation of European supercell thunderstorms at unprecedented scale and detail. Utilizing advanced computational modeling capable of resolving atmospheric structures as small as 2.2 kilometers, the team generated an eleven-year simulation spanning 2010–2021, which was then meticulously cross-verified against real-world radar observations. This represents a crucial advancement over conventional climate models, which typically lack the spatial fidelity needed to resolve the fine-scale processes responsible for the formation and evolution of supercells.

The findings reveal that the Alpine region continues to act as a persistent “hotspot” for supercell activity, with approximately 38 events per season on the northern slopes and 61 on the southern side under present-day climate conditions. However, as atmospheric temperatures increase by 3 degrees Celsius above pre-industrial levels—a realistic projection under many climate warming scenarios—this already significant storm activity intensifies dramatically. The simulations predict up to a 52% increase in supercell occurrences north of the Alps and 36% on the southern flanks. Such an amplification implies more frequent episodes of hazardous weather that pose dire risks to populated areas and vulnerable natural systems situated within this mountainous corridor.

Central and Eastern Europe are also projected to witness a notable escalation in supercell storms, while some regions such as the Iberian Peninsula and southwest France may experience a decline in frequency. This heterogeneous regional response underscores the complex and differential impacts of climate change across the continent, shaped by local topography, atmospheric circulation patterns, and land-atmosphere interactions. These insights challenge any simplistic notion of uniform climate effects, instead highlighting the importance of detailed, location-specific projections to inform mitigation and adaptation strategies effectively.

The ability to track European supercell thunderstorms using weather radar networks currently faces significant challenges owing to inconsistency and fragmentation between the radar systems of different countries. Such gaps hinder seamless cross-border storm detection and analysis. The novel high-resolution model employed by the research team uniquely overcomes these observational blind spots by simulating individual storm cells with great precision and continuity across national boundaries. While the model captures the majority of storms matching or exceeding 2.2 kilometers in scale persisting longer than an hour, it naturally excludes smaller, ephemeral convective events that are nonetheless part of the broader thunderstorm climatology.

From a methodological perspective, the scClim project’s state-of-the-art climate model integrates refined representations of atmospheric convection dynamics coupled with robust climate forcing scenarios. This allows for nuanced explorations of how supercells respond to elevated greenhouse gas concentrations and resultant thermal regimes. By simulating hundreds of realistic supercell storm cycles over more than a decade, the research provides statistically significant projections of future storm frequency and intensity patterns. This stands in stark contrast to prior investigations limited primarily by lower temporal resolution or incomplete storm lifecycle data.

Despite their relatively rare occurrence compared to other forms of convective storms, supercells disproportionately contribute to severe weather-related damage. Their fast-moving, highly organized nature enables them to produce phenomena such as destructive hail swaths, damaging wind gusts, and flash flooding, thereby imposing extensive socio-economic costs. Current weather risk assessments and disaster preparedness protocols frequently overlook these extreme events or treat them as outliers. The illuminated increase in supercell occurrence poses significant new challenges for European emergency planning, infrastructure resilience design, and agricultural risk management.

The Alpine region’s designation as a supercell “hotspot” aligns with its unique atmospheric conditions that favor convective storm initiation and maintenance. Orographic lifting along mountain slopes enhances vertical air motion, while abundant summer moisture supplies energy to feed storm development. As the climate warms, these factors intensify, potentiating both the frequency and severity of damaging storms. The direct implications for the densely inhabited and economically critical regions adjacent to the Alps are profound—rising thunderstorm activity threatens to exacerbate infrastructure strain, disrupt transport networks, and cause substantial crop losses.

Forecasting improvements afforded by high-resolution climate simulations offer a promising avenue for enhancing early-warning systems and risk mitigation measures. By better resolving supercell formation and progression mechanisms, meteorologists will be able to identify imminent storm threats more accurately and with longer lead times. Over time, this can translate into more effective public advisories, optimized emergency response actions, and ultimately fewer casualties and property damages. Nonetheless, realizing these benefits requires sustained investment in computational resources, data assimilation techniques, and cross-border integration of meteorological networks.

On a broader scale, the research highlights the critical importance of integrating supercell thunderstorms within climate change risk frameworks. These violent storms are among the leading contributors to thunderstorm-related hazards, yet they remain underrepresented in policy discussions and resilience planning. Awareness of their potential future intensification should galvanize both policymakers and the public to prioritize climate mitigation efforts alongside localized adaptation measures. Improved understanding of the atmospheric conditions conducive to supercell genesis will be instrumental in refining vulnerability assessments and guiding infrastructure development to withstand escalating weather extremes.

Looking forward, continued advancements in modeling capabilities and observational networks will be essential to monitoring the evolution of supercell thunderstorms across Europe. The combination of physical climate changes, regional atmospheric circulation shifts, and land use modifications will collectively modulate their incidence and intensity. As demonstrated by this pioneering study, realistic simulations capturing mesoscale meteorological processes form the backbone for comprehending and anticipating these complex interactions. Accordingly, ongoing interdisciplinary collaboration among climate scientists, meteorologists, and risk management experts remains vital to safeguard European communities from this mounting climatic threat.

The urgency of this research resonates beyond academic circles. As extreme weather events grow ever more commonplace under global warming, understanding specific contributors like supercell thunderstorms equips society with actionable intelligence to confront emerging challenges. Increased storm frequency and severity portend not only economic and infrastructural consequences but also profound human costs in terms of safety and well-being. The stakes could hardly be higher, making the integration of cutting-edge climate modeling and comprehensive storm forecasting an indispensable pillar of future climate resilience strategies.

By shedding light on the granular dynamics of European supercell thunderstorms and their response to warming scenarios, this research opens new frontiers in both meteorology and climate science. It exemplifies how computational prowess combined with interdisciplinary collaboration can overcome prior observational limitations to deliver insights of critical societal relevance. As Europe braces for a future shaped by intensifying storms, such work signals a turning point in our capacity to anticipate, understand, and ultimately adapt to one of nature’s most formidable forces.

Subject of Research: Computational simulation/modeling of European supercell thunderstorms under climate change scenarios

Article Title: European supercell thunderstorms – A prevalent current threat and an increasing future hazard.

News Publication Date: 27-Aug-2025

Web References: DOI 10.1126/sciadv.adx0513

Image Credits: © MeteoSwiss, Luca Panziera

Keywords: supercell thunderstorms, climate change, high-resolution climate modeling, Europe, Alps, severe weather, storm simulation, mesocyclone, atmospheric convection, risk assessment