Methodology for the constitution of a restricted set of heatwaves, derived from climate projections, that can be used for building performance simulations

In the context of climate change, Building Performance Simulations are used to assess the ability of passive buildings to maintain acceptable comfort conditions, or to limit the air conditioning energy consumption during heatwaves. Climate projection data, including heatwaves, are needed to feed the Building Performance Simulation tools. A building, located in a given location, is likely to experience several heatwaves with different characteristics in the coming decades. There is a need to develop a methodology dedicated to the constitution of heatwave weather files datasets, that are representative of the local meteorological diversities, and that are sufficiently reduced to limit the number of required simulations to assess building performances. This is the objective of the 4-step methodology described in this article. The methodology is tested for the location of Lyon Saint-Exupéry airport, France. The first two steps consist in collecting climate projection data, and detecting heatwaves contained in these data. For Lyon Saint-Exupéry airport, 2384 heatwaves were detected. The last two steps consist in characterizing the heatwaves and selecting a set of distinct heatwaves, representative of the meteorological diversity of a given location. For Lyon, the methodology identified 10 distinct heatwave groups using an agglomerative hierarchical clustering method.