Meteorological conditions within the microenvironments surrounding buildings can deviate significantly from data recorded at local weather stations. This study investigated the impact of the built environment on local weather data and its subsequent effect on building energy performance. A comparative analysis was performed of four weather data sources: a rooftop weather station on the University of Colorado Boulder campus (CU), two airport weather stations in Boulder (BMA) and Denver (DIA), and Typical Meteorological Year (TMY) data. The analysis revealed a strong correlation for dry-bulb air temperature (T dry ) and dew point temperature (T dew ) among the CU, BMA, and DIA stations. The CU station recorded a dry-bulb air temperature approximately 1.7°C higher than BMA. The most significant deviations were observed in solar radiation and wind speed measurements. The TMY, CU, and BMA datasets were used to assess the impact of weather data selection on the energy performance prediction of a benchmark low-rise office building that is impactable by both ambient climate and internal loads. The total site energy prediction was not affected notably by different weather inputs. Simulations for 2015 using CU data showed a 20 % reduction in heating load and a 14 % increase in cooling load compared to BMA data. For 2020, the CU data resulted in a 66 % lower heating load and a 15 % higher cooling load than BMA. Although this study is based on a single location and building type, it clearly demonstrates (1) microenvironment change is marginal in T dry and T dew but significant in local solar and wind; (2) the microenvironment impact of the tested building and climate is trivial on total energy consumption but notable on heating and cooling energy. This conclusion is more neutral than biased towards the directions of either emphasizing or discarding microclimate impacts commonly found in literature.
Zhai et al. (2026) studied this question.