Impact of climate change on degradation risks in solid masonry walls: Uncertainty assessment using a multi-model ensemble.

In climate science, the impact of climate change is assessed through multiple climate models. Usually, hygrothermal analyses use one climate model, making the results only valid for this -highly uncertain-climate evolution, which cannot be generalised. The robustness of the climate change impact on building envelopes is unknown. Therefore, we implemented a multi-model ensemble in hygrothermal simulations for the first time. This paper presents 2160 hygrothermal simulation results to assess the change in degradation risks in solid masonry walls in Hamburg for 10 global-regional climate model chains. Firstly, the results are analysed in 8 ways, each featuring different information on the climate change impact, ensemble spread, and robustness. In Hamburg, the ensemble spread is assessed for the percentage of cases (i.e. building and exposure parameter combinations) with an in(de)creasing risk. For freeze-thaw damage, the spread is 52 % (69 %), indicating a high uncertainty. For wood decay in embedded beam heads, the spread is 28 % (18 %). The smallest spread, and most robust impact, is found for mould growth: 19 % (10 %). Secondly, a methodological framework to determine the ensemble size as a trade-off between accuracy and computational demand is presented. The superior level, i.e. most detailed at high computational cost, requires minimum 10 ensemble members. The minimum level applies one climate projection. The advanced level requires 3 ensemble members, providing limited information on the robustness of the climate change impact. To conclude, climate models introduce uncertainty in the climate change impact on building envelopes. Multi-model ensembles should become state-of-the-art in hygrothermal modelling. [Display omitted] • Robustness of climate change impact on built environment was previously unknown. • A multi-model ensemble is used to study uncertainties of changing degradation risks. • 130-year time series are evaluated for 10 global-regional climate model chains. • Up to 21 % (77 %) of the cases indicate an in(de)creasing freeze-thaw risk in Hamburg. • A framework is developed to determine the ensemble for climate impact studies. [ABSTRACT FROM AUTHOR]