ABSTRACT We present UCanWBGT, a heat stress model for estimating wet‐bulb globe temperature (WBGT) in an infinitely long street canyon. Radiative transfer within the canyon is calculated analytically from downward fluxes and surface temperature to determine the mean radiant temperature for a black globe. In combination with a standard set of meteorological fields, WBGT is determined via an empirical equation, resulting in a computationally efficient approach suitable for inclusion in numerical weather prediction (NWP) and climate models. For validation, we apply UCanWBGT to high‐resolution NWP output over Paris during a heatwave event and compare this with WBGT values derived from black‐globe thermometer observations made in street canyons during the PANAME project. UCanWBGT performs well, capturing daily variations in WBGT and representing transitions between sunlit and shaded conditions. Discrepancies are linked to forecast errors in meteorological fields and assumptions associated with the street canyon. Sensitivity tests reveal that modifying the canyon geometry affects the degree (and timing) of shading experienced in the canyon, and neglecting the urban geometry (representing it as a flat plane) eliminates the representation of daytime shading and reduces WBGT enhancement via reflections within the canyon. WBGT is also highly sensitive to meteorological fields, particularly temperature and humidity, although less so to the albedo and emissivity of the canyon facets. We conclude by demonstrating a practical application of UCanWBGT. Using NWP simulations for August 10, 2024, we estimate WBGT along the marathon route at the 2024 Paris Olympics and, using published safety thresholds, identify timing and routing strategies that minimise heat‐stress risks for athletes. We identify a period of high risk through the middle of the day, noting that the event would best be scheduled outside this period. Also, for daytime events, increased routing through urban areas and forest roads reduces risk, while for nighttime events rural areas are preferable.
Shonk et al. (Sun,) studied this question.