Socioeconomic development influences both the drivers and consequences of climate change, but many scenario applications still rely on highly aggregated indicators such as GDP and population, which mask regional diversity. This study develops spatially explicit socioeconomic scenarios for Germany to support climate action and land-use planning with greater detail and contextual relevance. Using a mixed-methods framework, we integrate historical trend analysis, participatory scenario building, and quantitative projection to generate annual trajectories of key indicators at district level from 2020 to 2100. The indicators cover human, social, financial, and manufactured capital, including demographic dynamics, education, income, employment, inequality, and social cohesion. We analyse the dataset with correlation and clustering methods to explore interdependencies and to identify distinct regional development pathways. Results highlight persistent associations between income, education, and life expectancy, but also scenario-specific changes in the relations between inequality, employment, and urbanisation. Strong east–west disparities and urban–rural contrasts remain across all scenarios, while a sufficiency-oriented pathway demonstrates that wellbeing gains can occur without economic growth. By providing high-resolution, multidimensional socioeconomic scenarios, this study enhances integrated climate–land modelling and informs the design of regionally adaptive and socially equitable climate policies under multiple plausible futures.
Winkler et al. (2026) studied this question.