Using Clustering to Understand Intra-city Warming in Heatwaves: Insights into Paris, Montreal, and Zurich

Abstract

We introduce a novel methodological advancement by clustering paired near-surface air temperature with the planetary boundary layer height (PBLH) to characterize intra-city clusters for analytics. To illustrate this approach, we analyze three heatwaves (HW): the 2019 HW in Paris, the 2018 HW in Montreal, and the 2017 HW in Zurich. We assess cluster-based characteristics before, during, and after heatwave events. Using the objective hysteresis model, we determine the overall strength coefficient of the hysteresis loop between ground storage flux and all-wave downward radiative flux, ranging from 0.414 to 0.457 for urban clusters and from 0.126 to 0.157 for rural clusters during the heatwave periods. Across all cities, we observe a consistent refueling-restoration mode in the cumulative ground heat flux as the heatwaves progress. Future developments of this proposed two-component clustering approach, with the integration of more influential physics, will offer a more comprehensive characterization of cities for urban climate analytics.