ABSTRACT The variation of seasonal characteristics driven by climate change introduces emerging risks across various sectors, including energy management, agriculture, public health and urban planning. Traditional methodologies employed to determine seasonal ‘severity’ often suffer from a dual challenge: they either require excessively complex datasets or fail to adequately represent abrupt intra‐seasonal temperature fluctuations. This study introduces the Winter–Summer Severity Index (WSSI), a newly developed metric designed to measure seasonal intensity across 15 major European cities while ensuring high accuracy with minimal data input. The WSSI innovatively integrates the widely utilised ‘degree‐day’ approach with the ‘Standardized Temperature Index’ (STI). The hybrid framework enables the calculation of seasonal temperature anomalies cumulatively and their subsequent standardization into comparable numerical data. For the analysis, the high‐resolution ERA5‐Land reanalysis dataset was utilised, spanning 75 years from 1951 to 2025. The analytical process was conducted using daily minimum temperatures for winter and daily maximum temperatures for the summer season severity. One of the most critical findings of this study is the high degree of consistency the index demonstrates with historical data. The WSSI application accurately captured landmark extreme events in European climate history, such as the 2003 Western European heatwave and the 2012 Eastern European cold wave. Index values reached statistically extreme levels during these periods, confirming that the method successfully represents not only general trends but also outlier events. The results indicate a systematic decrease in winter season severity (a warming trend) across Europe. Conversely, summer intensity has increased significantly in nearly all cities considered—except Istanbul—showing a particularly pronounced intensification in Mediterranean cities such as Madrid and Rome. In conclusion, the WSSI distinguishes itself as a reliable decision‐support tool for climate change adaptation due to its ability to generate rapid results with limited data and its proven historical consistency. While providing a practical instrument for energy management and agricultural planning, WSSI also serves as a vital data source for tracking the local footprints of teleconnection patterns, validating seasonal forecasts and defining robust climate adaptation strategies.
Aksu et al. (Mon,) studied this question.