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The Influences of Political Affiliation and Weather-Related Impacts on Climate Change Adaptation in U.S. Cities

Rachel M. GurneyaUniversity of Wisconsin–Madison, Madison, Wisconsin

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Sisi MengbUniversity of Notre Dame, Notre Dame, Indiana

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Samantha RumschlagbUniversity of Notre Dame, Notre Dame, Indiana

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Alan F. HamletbUniversity of Notre Dame, Notre Dame, Indiana

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Abstract

This study examines the influences of state and local political affiliation and local exposure to weather-related impacts on local government climate change adaptation efforts in 88 U.S. cities. Although climate adaptation takes place when cities replace critical infrastructure damaged by severe weather events, little is known about the influence of political affiliation and severe weather events on climate adaptation in a broader sense. Using multiple linear regression models, this study analyzes variations in local government climate adaptation efforts as a function of local gross domestic product (as a control variable), historical weather-related factors [i.e., number of extreme weather events, weather-related economic impact due to property damage, and weather-related human impact (injuries and fatalities)], and state and local political affiliation. The findings of this study indicate that local political affiliation significantly influences local government climate adaptation efforts; however, state political affiliation does not. Further, local weather-related impacts do not appear to affect the likelihood of local government to engage in climate adaptation efforts, even when accounting for potential interactions with local political affiliation. These results support the hypothesis that local political affiliation is a strong and robust predictor of local climate adaptation in U.S. cities. This study contributes to literature aimed at addressing the widely acknowledged need for understanding key barriers to U.S. climate adaptation, as well as the role of politics in moderating climate action.

© 2022 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Rachel M. Gurney, rgurney@wisc.edu

Abstract

This study examines the influences of state and local political affiliation and local exposure to weather-related impacts on local government climate change adaptation efforts in 88 U.S. cities. Although climate adaptation takes place when cities replace critical infrastructure damaged by severe weather events, little is known about the influence of political affiliation and severe weather events on climate adaptation in a broader sense. Using multiple linear regression models, this study analyzes variations in local government climate adaptation efforts as a function of local gross domestic product (as a control variable), historical weather-related factors [i.e., number of extreme weather events, weather-related economic impact due to property damage, and weather-related human impact (injuries and fatalities)], and state and local political affiliation. The findings of this study indicate that local political affiliation significantly influences local government climate adaptation efforts; however, state political affiliation does not. Further, local weather-related impacts do not appear to affect the likelihood of local government to engage in climate adaptation efforts, even when accounting for potential interactions with local political affiliation. These results support the hypothesis that local political affiliation is a strong and robust predictor of local climate adaptation in U.S. cities. This study contributes to literature aimed at addressing the widely acknowledged need for understanding key barriers to U.S. climate adaptation, as well as the role of politics in moderating climate action.

© 2022 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Rachel M. Gurney, rgurney@wisc.edu
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