This research explores using Destination Earth (DestinE) services as a digital twin framework to model and analyse Urban Heat Island (UHI) effects at the city level in extreme climate contexts. Focusing on Riyadh, Saudi Arabia, alongside neighbourhoods in Jeddah and Dhahran/Dammam for comparative analysis, the study integrates diverse data sources and machine learning techniques to simulate UHI patterns and assess nature-based solutions for urban cooling. The framework combines DestinE’s computational power and FAIR data principles to enable scenario testing through direct integration or local deployment within city-managed digital twins. This approach aims to support urban planners and decision-makers with scalable, data-driven insights to enhance climate resilience in rapidly urbanising, heat-stressed cities.