EGU26-17616, updated on 14 Mar 2026
https://doi.org/10.5194/egusphere-egu26-17616
EGU General Assembly 2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Poster | Wednesday, 06 May, 10:45–12:30 (CEST), Display time Wednesday, 06 May, 08:30–12:30
 
Hall X5, X5.156
Drivers of Uneven Urban Heatwave Hazard Across Europe: Mechanisms and Risk Assessment
Yu-Feng Chen and Christina W. Tsai
Yu-Feng Chen and Christina W. Tsai
  • National Taiwan University, College of Engineering, Department of Civil Engineering, Taiwan (peter12171217@gmail.com)

Europe has experienced more frequent and severe heatwaves under continued warming, but the associated hazard has increased unevenly across cities. We ask what drives contrasts across cities and how these contrasts should be reflected in heat risk assessment, focusing on 36 major European cities.

We estimate Heatwave Intensity Duration Frequency (HIDF) using a block maxima approach. Specifically, for each city and duration, we extract annual maxima of heatwave intensity and fit HIDF separately for two multi-decadal periods (1950–1994 and 1995–2024). We then quantify the hazard shift and rank cities by the magnitude of change; in our current ranking, Milan, Paris, and Brussels exhibit the most significant increases, whereas Oslo, Stockholm, and Berlin show the smallest increases. To better understand why these contrasts emerge, we compute Heatwave Cumulative Intensity (HWC) and apply Time-Dependent Intrinsic Correlation (TDIC) to examine multi-scale, time-varying associations between HWC and candidate drivers.

Preliminary results indicate that several large-scale circulation indices (Arctic Oscillation, AO; North Atlantic Oscillation, NAO; East Atlantic pattern, EA; Scandinavian pattern, SCAND, etc.) exhibit broadly coherent associations across neighboring cities, even when hazard trajectories diverge. This pattern suggests that local conditions, such as soil moisture, dew point, and cloud cover, may play a significant role in modulating city-level hazard changes. Finally, following the IPCC AR5 framework, we integrate hazard derived from HIDF with exposure and a composite vulnerability index to produce risk-oriented mapping, highlighting areas where rising hazard coincides with high societal sensitivity.

How to cite: Chen, Y.-F. and Tsai, C. W.: Drivers of Uneven Urban Heatwave Hazard Across Europe: Mechanisms and Risk Assessment, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17616, https://doi.org/10.5194/egusphere-egu26-17616, 2026.