Integrating socio-economic dimensions into climate change hotspot identification

As climate impacts accelerate, ‘climate change hotspots’ (CCHs) are increasingly used to prioritise limited adaptation resources. However, hotspot conceptualisation remains fragmented. To address this gap, this study first conducts an evidence synthesis of 353 studies to investigate how CCHs are conceptually defined and analytically identified across four major climate hazards (heat, drought, flood and snow). This synthesis shows that most existing hotspot methodologies are dominated by potential hazard intensity, while socio-economic dimensions, stakeholder knowledge and impact-based validation are rarely integrated. To address this knowledge gap, we develop a bottom-up integrated framework for CCHs identification. Transitioning away from a top–down hazard-centric approach, our bottom-up approach integrates biophysical and socio-economic data with event-based storylines and stakeholder consultation. The transferability of our framework is demonstrated through two European case studies, snow avalanches in Alps and Carpathians, and flash flood in Trentino-Alto Adige, Italy. The case studies identify hotspots by intersecting climate hazard data with local geographic characteristics and socio-economic information. In both applications, historical event-based storylines ground quantitative risk classifications in real-world disaster dynamics, while stakeholder consultations refine the localised exposure. The results reveal that Alpine and Carpathian snow hotspots are projected to persist and intensify by 2100. The flash flood hotspots remain concentrated in alluvial valley bottoms, where the hazard converges with dense socio-economic and infrastructural exposure. Our integrated framework provides an adaptable and transferable approach for identifying CCHs. It can serve as good practice and can support the prioritisation of adaptation effort and planning across administrative regions and sectors.