Doctoral Dissertation Research: Fingerprints of Global Warming in Worldwide Public Attitudes

这项研究将使用当地气候变化作为自然实验的刺激因素，以测试个人对当地异常气候的体验与对长期气候变化幅度的态度之间的预测关系。从俄罗斯2010年史无前例的热浪到美国东北部的“大雪末日”，异常天气模式经常被引用为气候变化存在或不存在的证据。围绕这些事件的叙述表明，公众舆论可能会受到最近和正在进行的天气的影响，但这一假说尚未得到系统研究。在这个项目中，广泛收集了多个国家的民意调查和学术调查，并使用一种新的方法--空间微观模拟--与历史气候指标相结合，以创建一个关于当地气候变化对世界各地公众态度的影响的模型。然后，使用全球模型对气专委排放情景所预测的当地气候变化下未来公众态度的模式进行预测性比较。这项研究旨在推进贝叶斯空间分析方法和人类对慢性危险的风险感知和适应的理论理解。这一新的方法利用广泛收集的现有数据来解决有关人类对气候变化的感知和反应的关键理论问题。以前的观察性或实验性研究很少涉及明显的气候经验在形成对气候变化影响的态度方面的作用。这项研究基本上是跨学科的，使用地理信息科学的方法将心理学的理论与气候学和社会科学数据相结合。局部气候异常是否会影响个人对气候变化的态度？如果是这样的话，随着人们越来越多地经历全球变暖的影响，人们的态度将随着时间的推移而发生怎样的变化？尽管个人体验环境现象的方式在态度形成和行为反应中发挥了重要作用，但人们如何看待气候变化等慢性危害，以及这些经历在多大程度上影响态度和行为，目前尚不清楚。为了解决这一差距，这项研究试图解释个人气候经历对气候变化态度的影响。如果气候变化的经历被认为是全球变暖的积极或消极证据，它可能会影响个人对气候变化的态度以及缓解或适应的决定。个人行为变化是潜在温室气体减排的一个主要来源，该项目的结果将有助于解释影响这种变化的态度的决定因素。通过将结果与未来气候预测相结合，该项目可以促进预测气候变化影响、风险认知和缓解行为之间的正面或负面反馈。了解此类行为的决定因素将是气候变化政策和风险沟通的关键组成部分。

This research will use local climate variability as the stimulus for a natural experiment to test for a predicted relationship between individual experience of anomalous local climate and attitudes about the magnitude of long-term climate change. From Russia's unprecedented 2010 heat wave to the northeastern U.S. "snowpocalypse," abnormal weather patterns are often cited as evidence for or against the existence of climate change. The narratives surrounding these events suggest that public opinion may be influenced by recent and ongoing weather, but this hypothesis has not yet been systematically investigated. In this project a broad multi-country collection of public opinion polls and academic surveys is coupled with historical climate indicators using a new methodology, spatial microsimulation, to create a model of the effect of local climate variability on worldwide public attitudes. The global model is then used to generate predictive comparisons of future patterns of public attitudes under the local climate changes projected by the IPCC emissions scenarios. This research is designed to advance both the methodology of Bayesian spatial analysis and the theoretical understanding of human risk perception and adjustment to chronic hazards. This novel methodology takes advantage of a broad collection of existing data to address critical theoretical questions about human perception and response to climate change. Few previous observational or experimental studies have addressed the role of manifest climate experience in attitude formation about the effects of climate change. The research is fundamentally interdisciplinary, integrating theory from psychology with climatology and social science data using methods derived from Geographic Information Science.Do local climate anomalies influence individual attitudes about climate change? If so, how will attitudes change over time as the impacts of global warming are increasingly experienced? Although the ways in which individuals experience environmental phenomena play a major role in attitude formation and behavioral response, it is unclear both how people perceive chronic hazards such as climate change and to what extent those experiences influence attitudes and behaviors. To address this gap, this research seeks to explain the effect of individual climate experience on attitudes about climate change. If the experience of climate variability is perceived as positive or negative evidence of global warming, it may influence individual attitudes about climate change and decisions to mitigate or adapt. Individual behavior change represents a major source of potential greenhouse gas emissions reductions, and the results of this project will help to explain the determinants of attitudes that shape such changes. By combining the results with future climate projections, this project can facilitate prediction of positive or negative feedbacks between climate change impacts, risk perceptions, and mitigation behavior. Knowledge about the determinants of such behavior will be a critical component of climate change policy and risk communication.