Pieter Groenemeijer

Extreme Wind Events in Europe:

Meteorological Mechanisms, Forecasting Challenges and Impacts

Pieter Groenemeijer is a meteorologist and physicist, and Director of the European Severe Storms Laboratory (ESSL). His research focuses on severe convective storms, including hail, tornadoes, and thunderstorms, with particular emphasis on forecasting methods, nowcasting techniques, and climatological analysis of extreme weather events across Europe. He obtained a Master’s degree in Meteorology from Utrecht University and a PhD in Physics from the Karlsruhe Institute of Technology, where his doctoral research addressed convective storm development in contrasting thermodynamic and kinematic environments. Since 2011, he has led ESSL, playing a central role in advancing European research on severe weather. He has contributed significantly to the development and scientific exploitation of the European Severe Weather Database (ESWD), a key resource for the collection, validation, and analysis of severe weather reports. His work integrates observational data, radar and satellite products, and numerical modeling to improve the understanding and prediction of convective hazards. In addition to his research activity, he has been actively involved in training programs and testbeds for forecasters, fostering collaboration between research and operational meteorology and supporting improved risk assessment and early warning capabilities across Europe.

Extreme wind events are among the most destructive natural phenomena, posing significant risks to infrastructure and human life. For wind engineers and meteorologists, understanding not only the intensity of these extremes but also their spatial and temporal occurrence is important. The lecture will delve into the meteorological backgrounds of extreme wind events, exploring why and where they occur, their forecasting, morphology and what this means for their impacts. Wind extremes are broadly categorized into synoptic-scale windstorms and convective gusts, each driven by distinct atmospheric processes. Synoptic-scale events are often associated with large weather systems, while convective gusts, including tornadoes, downbursts, and derechos, arise from deep-moist convection. These convective events are particularly challenging to predict due to their small spatial and temporal scales. Borderline cases between synoptic and convective events further complicate classification, analysis and forecasting. Geographically, Europe experiences varying frequencies of severe wind events. Italy, particularly its northern regions, reports the highest incidence of tornadoes, with ongoing efforts by the European Severe Storms Laboratory and its volunteer partners such as PreTEMP to document and assess historical events. Severe wind gusts are harder to track due to underreporting of less damaging events. Climate change scenarios suggest an upward trend in severe storms in northern Italy, particularly for large hail events, which often accompany strong winds. While the trend for tornadoes remains unclear, convective instability and wind shear play critical roles, with the latter showing limited change over time. A closer examination of specific cases, such as tornadoes and bow echoes, reveals the complexity of their wind fields. Some wind events, for instance, exhibit both straight-line wind properties and vortex structures. Despite advances in numerical weather prediction, the predictability of convective storms remains low. Ensemble simulations, which introduce perturbations in model physics or initial conditions, provide probabilistic forecasts, but their accuracy diminishes with increasing lead time, converging toward climatological averages. Some systematic errors in convection-permitting models persist, posing ongoing challenges for weather services. State-of-the-art forecasting combines high-resolution modelling and diagnosis through environmental characteristics, such as moisture, lift, instability, and wind shear, concepts with a specific meaning in meteorology. For downbursts, negative buoyancy, driven by water loading, and evaporation or melting of water creates strong downward momentum, while horizontal transport of vertical momentum can dominate in some scenarios. Tornadoes, on the other hand, rely on the generation of intense vertical vorticity near the surface, often through the tilting of vortex lines in supercells. Recent research suggests that tornadoes develop upward from the ground where the concentration of vorticity through various processes first takes place. Using this approach of analysing environmental characteristics ESSL has developed algorithms using hazard ingredients for experimental forecasts in up to 10 days ahead. Zooming in to the small-scale structure of tornadoes and downbursts, we see important differences among tornadoes, a topic reported on the foundational work of Ted Fujita, who introduced the widely recognized Fujita scale for tornado intensity, and its many derivatives. For example, the inner structure of tornadoes varies with the swirl ratio and contains highly volatile three-dimensional winds. When assessing the impact of winds on structures, it is crucial to match the scale of the wind field in tornadoes and downbursts with that of the affected infrastructure. Evidence indicates that wind speeds reached in fractions of a second are responsible for most damage, raising questions about the adequacy of the standard gust definition based on 3-second averages of its horizontal component at 10 meters above ground. To address these discrepancies, ESSL introduced the International Fujita Scale, defining wind speed as the instantaneous three-dimensional wind at the height of damage. This approach aligns more closely with speeds measured by Doppler radar, photogrammetry evidence, and engineering calculations than the Enhanced Fujita Scale used in the United States. In conclusion, this presentation highlights the importance of integrating meteorological research, advanced modelling, and observational data to improve our understanding and forecasting of extreme wind events. Collaborative efforts at ESSL and beyond aim to refine predictive tools and better understand the impacts of these destructive phenomena on society and infrastructure.