From the Mundane to the Profound: Developing a Political Model of Weather Information Processing and Climate Change Beliefs

Abstract

This dissertation examines the relationships between the mundane, our daily habits of weather information collection, and the profound, our beliefs about climate change and relevant policy solutions. Climate change is a hotly contested, highly partisan policy issue which results in many conflicting models of information processing. Weather information, such as daily temperature and precipitation forecasts, on the other hand is much less controversial. However, this information is often portrayed in the context of climate information, relying on portrayals of averages and extremes over longer periods of time. This type of information can therefore bypass many of the filters, such as identity and emotion, that are frequently applied to climate and news information. Using a variety of cross-sectional quantitative analyses, I examine these relationships between the mundane, weather information, and the profound, climate change beliefs. Findings first suggest individual differences help explain patterns of usage of weather information. I also find that some, but not all, weather information sources are related to climate change beliefs and in varying ways. These findings suggest not all weather information is processed in the same manner; rather, some sources may activate relevant filters while others do not. Finally, I find that information and beliefs about climate change help explain policy preferences.