Abstract Urban areas are increasingly vulnerable to the impacts of climate change, with growing populations exposed to extreme weather. Understanding urban weather dynamics is essential, yet professional weather stations are often located outside cities, limiting their ability to capture urban‐specific phenomena. Crowdsourced data from privately owned “Crowd Weather Stations” (CWS) offers a promising alternative, providing dense spatial coverage to study processes like the urban heat island (UHI). While the UHI is commonly examined under ideal calm conditions, such scenarios are rare, and the role of wind in spreading urban heat to downwind areas is often overlooked. This study analyzes nocturnal urban heat advection (UHA) using five years (2019–2023) of crowdsourced weather data from Paris, France, and Berlin, Germany, from several thousand CWS. We first develop a framework to quantify the UHA effect from CWS data, taking into account the strength of the UHI during individual cases with respect to the average conditions. Results show that wind intensifies heat exposure significantly downwind of city cores, with the strongest effects at wind speeds around . The advection effect decreases gradually with distance from the urban core and varies with wind direction. These findings highlight the importance of accounting for UHA to improve our understanding of urban heat exposure and its spatial variability, particularly in downwind regions. This study provides a framework for utilizing dense crowdsourced data to link conditions in the atmospheric boundary layer better with those in the urban canopy layer.
Kittner et al. (Mon,) studied this question.