Digital twins drive demand for scenario planning

Extreme heating is one of the greatest climate risks facing many cities, especially in the tropics. But the complexity of interactions between a changing climate and a changing built environment means pulling together many sources of information and multiple models. That's the goal behind the Cooling Singapore center's “digital urban climate twin” (DUCT), which aims to help planners and policy makers to test the temperature impact under different future scenarios. The system "will incorporate information on buildings, traffic, vegetation, land surfaces and movement of people, as well as factors such as wind and sunlight."

This digital twin suggests that the cost and complexity of assembling application-specific digital twins will fall within the reach of cross-cutting initiatives at the metropolitan level, rather than requiring a large-scale coordinated effort over long periods of time across many organizations, and their main use will be to test possible decisions. This suggests that even as such models are likely to proliferate and produce good forecasts, they may compete or contradict each other, and ultimately serve to fuel a new kind of statistical or computational arms race among competing stakeholders if not accompanied by sound foresight, consensus-building, and decision-making practices.