Simplifying heat stress assessment: Evaluating meteorological variables as single indicators of outdoor thermal comfort in urban environments

Abstract

Biometeorological indices are used to identify outdoor thermal comfort, and require the measurement or simulation of multiple variables, which is resource-intensive. In this study, we explore the meteorological variables determining these indices and assess their role as alternative single indicators of heat stress in the outdoor urban environment. Based on model output from microscale simulations conducted within mid-latitude German cities under clear-sky summer conditions, we calculated Pearson correlation coefficients between the Universal Thermal Climate Index (UTCI) and influential meteorological variables throughout the diurnal cycle. Given the high impact of radiation on human thermal comfort, the strongest correlations during daytime occur with mean radiant temperature (MRT, 0.66 to 0.97) and incoming shortwave radiation (SWR, 0.62 to 0.92). Our study highlights the stronger surface temperature correlation (0.75 to 0.93) compared to the air temperature correlation (0.33 to 0.64), especially during daytime. During daytime, street-level exposure to SWR emerges as a more reliable indicator of thermal stress compared to air temperature under the summertime situations investigated. Our correlation analysis between UTCI, aggregated daytime SWR, and sky view factors reveals that daytime exposure of surfaces to SWR does not necessarily increase nighttime UTCI. Instead, longwave radiation (LWR) trapping plays a more dominant role in the domains we analysed. This study supports future research that utilizes machine learning to determine heat stress and outdoor human thermal comfort.