Typically in human-earth system modeling studies, feedbacks between the earth and human systems are analyzed by passing information between independent models. The reliance on existing Earth System Model outputs limits the ability to explore feedbacks under arbitrary scenarios and equally important limits the ability to explore large-scale uncertainty in these interactions. In this study we explore a wide range of climate uncertainties and incorporate the implications of increased cooling hydrofluorocarbons emissions. We implement a statistical relationship between global mean temperature change and heating and cooling degree days that allows us to produce changes in building energy demands within GCAM at every time step and every region. While there is a general agreement in the literature that increasing temperatures will increase cooling energy demands and decrease heating energy demands, there has been no fully-coupled analysis of this dynamic that would, for example, account for the feedbacks on hydrofluorocarbons from increased cooling demands. The variation in the spatial distribution of temperatures leads to substantial variation in the change in cooling and heating energy across regions, with regions like USA, India and Sub-Saharan Africa experiencing a factor of two difference in cooling demands. While the feedbacks between building energy demand and global mean temperature are modest by themselves, this study prompts future research on coupled human-earth system feedbacks, in particular in regards to land, water, and other energy infrastructure.

通常在人地系统建模研究中，通过在独立模型之间传递信息来分析地球和人类系统之间的反馈。对现有地球系统模型输出的依赖限制了在任意情景下探索反馈的能力，同样重要的是限制了在这些相互作用中探索大规模不确定性的能力。在这项研究中，我们探索了广泛的气候不确定性，并纳入了冷却氢氟碳化合物排放增加的影响。我们实现了全球平均温度变化与加热和冷却度日之间的统计关系，这使我们能够在每个时间步长和每个区域在 GCAM 内产生建筑能源需求的变化。虽然文献中普遍同意升高温度会增加冷却能源需求并减少加热能源需求，但还没有对这种动态进行完全耦合分析，例如，解释因冷却需求增加而对氢氟烃的反馈. 温度空间分布的变化导致各地区制冷和供暖能源变化的显着差异，美国、印度和撒哈拉以南非洲等地区的制冷需求存在两倍差异。虽然建筑能源需求和全球平均温度之间的反馈本身是适度的，但这项研究促进了未来对耦合人地系统反馈的研究，特别是在土地、水和其他能源基础设施方面。