From static models to digital twins: a participatory framework for actionable climate adaptation modelling

Climate adaptation planning increasingly depends on advanced modelling and digital technologies to explore future risks and adaptation options under deep uncertainty. However, a persistent gap remains between the technical sophistication of climate and impact models and their usability, transparency, and relevance for real-world decision-making, particularly in the development of more complex modelling systems and Digital Twins for adaptation planning. This paper presents the Generic Adaptation Modelling Framework (GAMF), a structured, participatory approach for co-creating adaptation modelling systems. Developed through extensive stakeholder engagement, the GAMF details collaboration between modellers, end-users, and civil society across the full modelling lifecycle, emphasising modularity, reproducibility, transparency, and iterative learning. Two demonstrators—heat stress exposure in the Basque Country and coastal flood risk in Scheveningen—show how stakeholder-driven scoping, modular model integration, and co-designed outputs can improve the usability and relevance of quantitative adaptation modelling within the European context and beyond. The GAMF offers a transferable foundation for co-creating inclusive, decision-relevant modelling systems and Digital Twins that support equitable and actionable climate adaptation planning.