Are high-resolution urban datasets necessary for accurate heat exposure modelling in cities?

Climate change drives global temperature rises. In cities, where most people live, urbanisation further exacerbates how people experience this excessive heat. The resulting urban heat disrupts businesses, economies, and power grids on a large scale, while causing discomfort, heat stress and strain, and in severe cases, morbidity and mortality at the individual level. Climate models are a key tool in quantifying the multi-scale drivers and impacts of urban heat, as well as mapping its distribution in the city - required to future planning and mitigating negative impacts. However, to date, urban areas have not been realistically represented in climate models, while recent technological advancements have enabled measuring data on urban fabric and form at sub-metre scales. Despite these advancements, how detailed urban data should be for accurate heat exposure modelling is in question. To address this, we have designed four scenarios in the Weather Research and Forecast (WRF) model to examine the effect of locally measured versus global urban data as well as the processing method: local climate zones (LCZs) versus detailed gridded datasets. We then compare them with one scenario without considering intra-urban variabilities. Sydney is the case study. All the experiments are conducted using BEP-BEM-Comfort, an urban canopy model that outputs the subgrid-scale range of Universal Thermal Climate Index (UTCI) for a more comprehensive representation of human heat exposure. Together, these experiments guide urban representation choices for a more accurate heat modelling that in turn better informs large-scale policies for urban heat mitigation and adaptation strategies.