Impact of Spatially Continuous Urban Surface Properties on Heatwave Simulations: A Multi-City Analysis

Urban areas are unique in form and function, and representing them in process-based models requires prescribing facet-level morphological and radiative properties, among others. Most urban canopy models prescribe these by density class or local climate zone (LCZ), assigning identical values across broad regions or worldwide. However, properties can vary widely between and within cities. Global km-scale urban facet-level property datasets have recently emerged, but have seldom been applied in regional modeling. Here, we incorporate one such dataset, U-Surf, into the Weather Research and Forecasting (WRF) model, modifying it for WRF's multi-layer urban canopy model and releasing it as U-Surf-WRF. Considering 13 U.S. cities, U-Surf-WRF parameters vary more between LCZs than default WRF parameters, with consistently lower impervious fraction. To determine the effects of using U-Surf-WRF, we conduct high-resolution (1 km) WRF simulations of recent heatwaves for these 13 cities using default and U-Surf-WRF parameters. Either prescribed by LCZ or for each grid point, using U-Surf-WRF yields more accurate surface temperatures. It also generally decreases modeled urban air temperature and increases modeled urban humidity, yielding lower simulated urban heat and dry islands. Decomposing the impact of each U-Surf-WRF variable, we find that albedo is useful for daytime simulations, especially for air temperature, but that morphology and impervious fraction are most relevant, especially for surface temperature. This study demonstrates the importance of city-specific, facet-level urban properties in urban weather and climate simulations. Conversely, in WRF simulations with poorly constrained parameters, we suggest caution interpreting the magnitude and spatial variability of urban signals.