Quantifying Urban Morphology-Induced Uncertainty in Urban Meteorology and Heat Stress Simulations in Southern California

Accurate representation of land use and urban morphological parameters (UMPs), particularly building height, road width, and roof width, is critical for urban climate/weather modeling. The Weather Research and Forecasting (WRF) coupled with the Single-Layer Urban Canopy Model (SLUCM) has been widely used; however, few studies have quantified urban modeling uncertainties associated with UMPs in Los Angeles, a key metropolitan area. This study assesses the impact of UMPs on WRF–SLUCM simulations in Los Angeles and quantifies UMP-induced uncertainties in 2-m air temperature (T₂), relative humidity (RH), wind speed and other outputs by integrating Polynomial Chaos Expansion, Sobol sensitivity analysis, and Monte Carlo methods. We apply urban Local Climate Zone (LCZ) land use data and find that incorporating accurate UMPs based on Los Angeles County improves wind speed simulations compared with default LCZ UMPs. Uncertainty analyses reveal strong sensitivities of urban meteorology to 50% UMP perturbation. The resulting average standard deviations of 2-m air temperature are 0.02 K (day) and 0.23 K (night), while those of urban canyon temperature are 0.51 K (day) and 1.03 K (night). Wind speed uncertainties are also notable, reaching 0.42 m/s (day) and 0.27 m/s (night). Among UMPs, building height has the strongest influence on urban T2, RH, and wind speed. Furthermore, uncertainties in urban meteorology propagate into heat stress estimates, where different indices show different spatial patterns of uncertainty. These findings underscore the importance of accurately representing UMPs in urban climate/weather simulations and their implications for assessing urban heat stress.