- 1SMHI, Norrköping, Sweden (fuxing.wang@smhi.se)
- 2Linköping University, Linköping, Sweden
- 3KTH Royal Institute of Technology, Stockholm, Sweden
- 4University of Cape Town, Cape Town, South Africa
- 5The Gothenburg Region, Gothenburg, Sweden
- 6University of Michigan, Michigan, USA
With current temperature increase likely to miss Paris Agreement targets and rapid urbanization, cities worldwide face increasing vulnerability to unprecedented extreme climate events like heat waves and extreme precipitation. We will present a new project Urban Extreme Climate Adaptation Digital Twin (UrbExt DT) and the preliminary results. UrbExt DT aims to equip decision-makers with hectometer-scale climate data and new insights to respond effectively to unprecedented climate extremes, fostering resilience and sustainability in cities. This is achieved by a Digital Twin of urban climate systems that integrates an advanced convection-permitting regional climate model, machine learning-based climate emulators, and a contextual visual analysis interface. We will provide probable first occurrence time, characteristics and prevailing meteorological conditions for record-breaking climate extremes using unprecedented 100-metre scale climate data over urban areas. We will also explore the physical processes linking urbanization to future extremes, addressing several unresolved questions. The interactive interface allows users to adjust urban development scenarios to test various adaptation strategies. UrbExt DT focuses on Sweden and Africa but adopts a global perspective. By developing tools that work in both settings, the project addresses vulnerabilities in small, medium and large cities alike and lays the groundwork for global scalability.
How to cite: Wang, F., Vrotsou, K., Mirjalili, S., Lennard, C., Nilsson Keskitalo, E., Vinuesa, R., Nikulin, G., Aldama Campino, A., Ribeiro, I., Amorim, J., Döscher, R., Lind, P., Wang, Y.-C., Petersson, R., Reski, N., Navarra, C., Brown, N., and Nilsson, L.: Urban Extreme Climate Adaptation Digital Twin, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19945, https://doi.org/10.5194/egusphere-egu26-19945, 2026.