Current and newly built buildings will inevitably experience the effects of climate change, therefore, the design and performance of these buildings should consider weather data that includes some of the effects of climate change, instead of only using historical weather data. However, climate change weather data suitable for buildings performance simulation are typically unavailable.
This research presents a method to integrate climate change features into historical weather data to make suitable climate change weather data available for buildings performance simulation. The method separates hourly dry bulb temperature into three time series components to simplify the integration of three climate change features. The method adjusts the maximum and minimum monthly averages, the number of days with maximum temperature above a specified threshold, and the number of consecutive occurrences of days with maximum temperature above a specified threshold (heatwave). The research also presents the adjustment of monthly averages of global solar irradiation. Under the climate–changed weather conditions, the annual heating thermal energy decreases by 21%–22%, the annual cooling thermal energy increases by 29%–31%, and the combined heating and cooling thermal energy decreases by 4%–5% compared to the heating and cooling thermal energy under the current weather conditions. The results indicate that climate–changed weather data is necessary as historical weather data is insufficient for accurately assessing the energy performance of a building.