A Geospatial Framework for Efficient Urban Heat Island Modelling and Risk Assessment under Future Urban Climate Scenarios

The Urban Heat Island (UHI) effect, driven by anthropogenic environmental modifications, heightens heat risks in urban areas. Climate change is already accelerating global temperatures. This effect is being further exacerbated with rapid urbanization with the effects of UHI posing critical challenges to human health and urban infrastructure.  Urban planners and decision-makers require robust tools to quantify UHI effects under diverse climate and socioeconomic scenarios to address this. Currently, urban canopy models (UCMs) are implemented in numerical weather prediction models. They generate temperatures in urban areas at comparatively high resolutions that cannot be achieved with Regional Climate Models (RCMs). However, using UCMs coupled to atmospheric models is computationally expensive and requires users to acquire detailed urban canopy parameters (UCPs), which is arduous, especially for rapid future urban planning focussed scenario modelling.

This study introduces an innovative geospatial framework consisting of a GPU-based UCM implementation coupled with an in-canyon vegetation model. This framework streamlines the modelling process through a built-in geospatial toolkit capable of pre-processing UCPs from either openly available urban datasets or user-supplied high-quality data. The GPU-based implementation significantly enhances computational efficiency, enabling UHI simulations with a standalone UCM at high spatial resolutions. This framework empowers planners to simulate UHI under various future climate and urban development scenarios by integrating climate projections and socioeconomic data. The resulting UHI predictions can identify high-risk areas, prioritize adaptation strategies, and inform climate adaptation planning for rapidly expanding cities. This research provides a transformative yet practical approach to UHI modelling, equipping urban decision-makers with an accessible, high-performance tool to confront the challenges of climate-driven urban heat risks.