The relationship between outdoor microclimate and indoor building conditions requires the input of hourly weather data on the typical meteorological characteristics of the specific location. These data, known as typical meteorological year (TMY), are mainly deduced from the multi-year records of meteorological stations outside urban centres, preventing the actual complex interactions between solar radiation, wind speed, and high urban density. These factors create the urban heat island effect and higher ambient air temperatures, skewing the assumptions for energy demand in buildings. This paper presents a computational method for assessing the effect of the urban climate in the generation of typical weather data for dynamic energy calculations. As such, the paper discusses an evaluation method of pairing ENVI-met 4 microclimate and IES-VE building energy modelling software to produce a typical urban specific weather dataset (USWDs) that reflects the actual microclimatic conditions. The ENVI-met results for the outdoor microclimate conditions were employed to determine the thermal boundaries for the IES-VE, and then used to compute the building’s energy consumption. The energy modelling that employed the USWDs achieved better performance compared to the TMY, as the former had just a 6% variation from the actual electricity consumption of the building compared to 15% for the latter.