Numerical building models are typically forced with weather data from a limited number of “representative cities” or weather stations representing different climate regions. The use of representative weather stations reduces computational costs, but often fails to capture spatial heterogeneity in weather that may be important for simulations aimed at understanding how building stocks respond to a changing climate. We quantify the potential reduction in temperature and load biases from using an increasing number of weather stations over the western U.S. Our novel approach is based on deriving temperature and load time series using incrementally more weather stations, ranging from 8 to roughly 150, to evaluate the ability to capture weather patterns across different seasons. Using 8 stations across the western U.S., one from each IECC climate zone, results in an average absolute summertime temperature bias of ∼4.0 °C with respect to a high-resolution gridded dataset. The mean absolute bias drops to ∼1.5 °C using all available weather stations. Temperature biases of this magnitude could translate to absolute summertime mean simulated load biases as high as 13.5%. Increasing the size of the domain over which biases are calculated reduces their magnitude as positive and negative biases may cancel out. Using 8 representative weather stations can lead to a 20–40% bias of peak building loads during both summer and winter, a significant error for capacity expansion planners who may use these types of simulations. Using weather stations close to population centers reduces both mean and peak load biases. This approach could be used by others designing aggregate building simulations to understand the sensitivity to their choice of weather stations used to drive the models.

通常使用来自有限数量的“代表城市”或代表不同气候区域的气象站的气象数据来强制建立数字建筑模型。使用有代表性的气象站可降低计算成本，但通常无法捕获天气的空间异质性，这对于旨在了解建筑存量如何应对气候变化的模拟可能很重要。我们通过在美国西部使用越来越多的气象站来量化温度和负荷偏差的潜在降低。我们的新方法是基于使用越来越多的气象站（范围从8到大约150）推导温度和负荷时间序列来评估捕获不同季节的天气模式的能力。利用美国西部的8个站点，每个IECC气候带各1个站点，相对于高分辨率网格数据集，平均夏季绝对温度偏差为〜4.0°C。使用所有可用的气象站，平均绝对偏差降至〜1.5°C。如此大的温度偏差可能会转化为绝对夏季平均模拟负载偏差，最高可达13.5％。由于正偏差和负偏差可能会抵消，因此增加计算偏差的域的大小会减小其大小。使用8个有代表性的气象站可能导致夏季和冬季高峰期建筑负荷的20-40％偏差，这对于可能使用这些类型的模拟的容量扩展计划人员来说是一个重大错误。在人口中心附近使用气象站可减少平均和峰值负荷偏差。