A statistical method for assessing retrofitting measures of buildings and ranking their robustness against climate change

Evaluating the usefulness and the reliability of retrofitted buildings for future climate can be a challenging task, while different scenarios and uncertainties exist both for retrofitting buildings and future climate. This paper presents a method to assess and quantify the relative robustness of retrofitting measures on long term, while climate variations in different time scales, extreme conditions and uncertainties of climate change are considered. The applicability of the method is examined by comparing two energy retrofitting measures for the existing residential building stock of Stockholm, whose energy performance is numerically simulated during 1961-2100 for five climate scenarios. The considered climate uncertainties are due to downscaling climate data from five different global climate models. The relative robustness of the retrofitting measures are evaluated in five time scales; hourly, daily, monthly, annual and 20-year period. The presented method facilitates the assessment and ranking of retrofitting measures, using few numbers. It also generates an overall view about the relative performance of retrofitting measures in different time scales.