Mapping the Gap: Visualizing and Understanding Discrepancies Between Climate Extremes, Environmental Attitudes, and Political Action

▪Regional-level results: Correlations between regional heat-drought exposure and dependent variables are highest for Green voting (H2) and FFF protest (H3), especially in urban areas and Eastern Germany ▪Individual-level results: Heat-drought level has a weak positive effect on climate chance concerns (H1), but no significant effect on Green party support (H2) ▪Heatwave during SOEP interview shows partial positive significance ▪Strongest predictors: Education (+), female (+), Eastern Germany (–), migration background (–), age (–, partially U-shaped) ▪Geographically, urban-rural and East-West divides are stronger than climate exposure –but weather effects are still present! ▪Adding other climate extremes and weather events (e.g., floods, wildfires) ▪Relating weather data to the 1961–1990 baseline period to capture (relative) changes over time across different regional levels ▪Linking spatial and survey data at the LAU level ▪Improving statistical models (e.g., multilevel models, generalized additive models) Mapping the Gap: Visualizing and Understanding Discrepancies Between Climate Extremes, Environmental Attitudes, and Political Action Daniel Meyer1 Elisabeth Stürmer1 Torvid Kreisler2 1Competence Centre for Regional Development, Federal Institute for Research on Building, Urban Affairs and Spatial Development, Cottbus, Germany 2Department of Sociology, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany Contact Daniel Meyer [email protected] References: [1] Howe et al. (2019) doi.org/10.1088/1748-9326/ab466a; [2] Sisco (2021) doi.org/10.1016/j.cosust.2021.09.001; [3] Rüttenauer (2024) doi.org/10.1080/14616696.2023.2277281; [4] Fernando et al. (2025) hdl.handle.net/10419/319526; [5] Quoß (2025) doi.org/10.1007/s10584-02403842-y; [6] Valentim (2023) doi.org/10.31235/osf.io/m6dpg ▪Public awareness of climate change has grown around the world –yet climate opinion and action remain highly polarized ▪Limited understanding of the detailed spatial patterns and the extent to which geographic variation in climate opinion and behavior is influenced by exposure to climate extremes ▪Contribution to a growing, but inconclusive, literature on the link between extreme weather experience and peoples’ attitudes and behavior ([1]–[5]) ▪Does regional exposure to climate extremes influence individuals’ environmental attitudes and political action? ▪H1: Regional heat-drought exposure (↑) → Climate change concerns (↑) ▪H2: Regional heat-drought exposure (↑) → Green support/vote (↑) ▪H3: Regional heat-drought exposure (↑) → Fridays for Future protest (↑) Motivation and Research Question ▪Uni-/bivariate analysis on regional level (n = 400 German districts and 4,600 German municipal associations) ▪Multivariate analysis on individual level (n = 9,627–21,569 persons in Germany) ▪Regional heat-drought level as a combination of number of hot days and de Martonne dryness, DWD, 2018–2021 (= spatial proximity) ▪Heatwave during SOEP interview, DWD, 2022 (= temporal proximity) ▪Climate change concerns, SOEP, 2022 ▪Leaning towards the Greens, SOEP, 2022 ▪Vote share of the Greens, Federal Election, 2021 ▪Local Fridays for Future protest, Valentim (2023 [6]), 2018–2021 Dependent Variables Independent Variables Average Annual Number of Hot Days (≥ 30°C), 2018–2021, 1x1 km Grid Cells Share “Very Concerned” About Impacts of Climate Change, 2022, NUTS-3 Level Vote Share of the Greens (Second Vote), Federal Election 2021; Fridays for Future Protest (Yes/No), 2018–2021, LAU Level Difference Between Climate Change Concerns (in Deciles) and Heat-Drought Level (in Deciles), 2018–2022, NUTS-3 Level Logistic Regressions on Concerns About Climate Change (1 = “Very Concerned”) and Leaning Towards the Greens (1 = “Yes”), 2018–2022, Individual Level, Clustered Standard Errors Adjusted for 400 Districts Hypotheses Research Question Empirical Design and Data Conclusion and OutlookRegression Results on Individual Level Descriptive Results on Regional Level Next Steps © GeoBasis-DE/ BKG 2024