A Comparative Analysis of Different Future Weather Data for Building Energy Performance Simulation

The building energy performance pattern is predicted to be shifted in the future due climate change. To analyze this phenomenon, there an urgent need for reliable and robust weather datasets. Several ways estimating projection creating files exist. This paper attempts comparatively three tools generating datasets based on statistical downscaling (WeatherShift, Meteonorm, CCWorldWeatherGen) with one dynamical (a future-typical meteorological year, created using a high-quality reginal model). Four city of Rome are generated applied simulation mono family house apartment block as representative types Italian residential stock. results show that morphed have relatively similar operation predicting comfort buildings. In addition, discrepancy between them downscaled file revealed. analysis shows comes not only from different approaches but also by type. Therefore, finding resilient solutions buildings, care should taken methods developing datasets, regional localized becomes vital.