Abstract
This study examines how different approaches to generating Future Typical Meteorological Year (F-TMY) data influence both absolute performance predictions and comparative evaluation of early-stage façade design strategies. The analysis compares three weather file generation methods - dynamical downscaling through Regional Climate Models (RCM) and two statistical approaches (morphing implemented through CCWeatherGen and stochastic modelling implemented through Meteonorm) – to assess their impact on building thermal resilience predictions across three-time horizons (2020, 2050, 2080). Using a case study office building in the temperate climate of Turin, Italy, multiple thermal resilience indicators are evaluated, including energy use intensity, peak loads, indoor overheating degree, and heat release to the urban environment. The results reveal significant differences in absolute projections between the methods. For indoor overheating risk, CCWeatherGen projections exceed those of RCM by 300 % by 2080, indicating substantially different predictions of occupant thermal discomfort. In terms of peak cooling loads, RCM projects values 40 % higher than CCWeatherGen, while Meteonorm shows projections 70 % lower than CCWeatherGen by 2080, highlighting major discrepancies in system sizing requirements. For heat release to the urban environment, Meteonorm projections exceed RCM by 5 % in the future period, suggesting different implications for urban heat island mitigation strategies. These differences highlight significant methodological differences in predicting future building performance, especially for extreme conditions. However, despite these absolute differences, the comparative ranking of building envelope design strategies remains relatively consistent across methods. The analysis also reveals important trade-offs between performance objectives. For example, increasing the window-to-wall ratio up to 75 % produces opposing effects - reducing energy consumption through improved daylighting but significantly increasing the risk of overheating (48–56 % increase). These findings have significant implications for architectural practice and building performance modelling. While absolute performance predictions vary substantially between methods, the consistent ranking of design strategies provides reliable guidance for early-stage design decisions. Solar control measures emerge as the most effective strategy across all methods, offering designers confidence in prioritizing these elements regardless of climate data methodology. This research provides practical guidance for integrating climate adaptation into façade design while managing the inherent uncertainties in future climate projections