Toward advanced representations of the urban microclimate in building performance simulation

The present contribution is concerned with the potential of empirically-based methods to capture the microclimate variance across a city and its implications for the performance of buildings. We explore the possibility to explain microclimatic variance across an urban area based on geometric and semantic attributes of specific locations. We use high-resolution and dynamic weather data streams across numerous urban locations in the city of Vienna, Austria. Using advanced data extraction methods, the values of a number of urban attributes that are hypothesized to contribute to the urban microclimate variance (e.g. morphological factors, semantic properties of urban surfaces) are derived for these locations. The results point to possible correlations between location-based climatic conditions and distinct urban attributes that could be harnessed to formulate empirically-based algorithms for generating customized microclimatic boundary conditions.