Public perceptions of climate change in the United States are deeply rooted in cultural values and political identities. Yet, as the public experiences extreme weather and other climate change-related impacts, their perceptions of the issue may shift. Here, we explore whether, when, and where local climate trends have already influenced perceived experiences of global warming in the United States. Using a large national survey dataset (n = 13,607), we compare Americans’ experiences of climate with corresponding trends in seven different high-resolution climate indicators for the period 2008 to 2015. We find that increases in hot dry day exposure significantly increases individuals’ perceptions that they have personally experienced global warming. We do not find robust evidence that other precipitation and temperature anomalies have had a similar effect. We also use multilevel modeling to explore county-level patterns of perceived experiences with climate change. Whereas the individual-level analysis describes a likely causal relationship between a changing climate and individuals’ perceived experience, the multilevel model depicts county-level changes in perceived experience resulting from particular climate trends. Overall, we find that exposure to hot dry days, has a modest influence on perceived experience, independent of the political and socio-demographic factors that dominate U.S. climate opinions today.

在美国，公众对气候变化的看法深深植根于文化价值观和政治认同。但是，随着公众遭受极端天气和其他与气候变化相关的影响，他们对这一问题的看法可能会发生变化。在这里，我们探讨当地气候趋势是否，何时何地已经影响了美国对全球变暖的认识。使用大型国家调查数据集（n = 13607），我们将美国人的气候经验与2008年至2015年期间七个不同的高分辨率气候指标的相应趋势进行了比较。认为自己亲身经历了全球变暖。我们没有找到有力的证据表明其他降水和温度异常也有类似的影响。我们还使用多级建模来探索对气候变化的感知经验的县级模式。个人层面的分析描述了气候变化与个人感知经验之间的可能因果关系，而多层次模型则描绘了特定气候趋势导致的县层面感知经验的变化。总体而言，我们发现暴露于炎热干燥的天气对感知的体验有适度的影响，而不受当今美国气候观点中支配的政治和社会人口统计学因素的影响。个人层面的分析描述了气候变化与个人感知经验之间的可能因果关系，而多层次模型则描绘了特定气候趋势导致的县层面感知经验的变化。总体而言，我们发现暴露于炎热干燥的天气对感知的体验有适度的影响，而不受当今美国气候观点中支配的政治和社会人口统计学因素的影响。个人层面的分析描述了气候变化与个人感知经验之间的可能因果关系，而多层次模型则描绘了特定气候趋势导致的县层面感知经验的变化。总体而言，我们发现暴露于炎热干燥的天气对感知的体验有适度的影响，而不受当今美国气候观点中支配的政治和社会人口统计学因素的影响。