Advancing CLMU for regional urban climate simulations through WRF coupling: intercomparison with NOAH–SLUCM

Yuan Sun , Keith W. Oleson, Cenlin He, Zhonghua Zheng 

Urban areas are highly vulnerable to climate extremes, creating a pressing need for reliable modeling tools to support climate adaptation. The Weather Research and Forecasting (WRF) model is widely used for regional urban climate simulations, and incorporating an alternative urban scheme for long-term climate projections expands the available modeling options and supports more robust simulation outcomes. This study evaluates the performance of Community Land Model-Urban (CLMU) via WRF coupling (WRF-CLMU), in comparison with the default WRF single-layer urban canopy model (WRF-SLUCM). We take Greater Manchester, UK, as a testbed under a grid spacing of 1.2 km for the year 2022. Model performance is assessed using near-surface air temperature, relative humidity, and wind speed from three observational stations, along with land surface temperature (LST) from MODIS and VIIRS 1 km products. The results demonstrate that both models have comparable performance, while WRF-CLMU better captures extreme heat conditions on 16 July, the onset of the 2022 July heatwave, as indicated by 1-2°C higher daytime LSTs in the main urban area. On the first day of the heatwave, it simulates daytime surface urban heat island intensity of 9.0°C, in agreement with the satellite-based estimates from MODIS (9.0°C) and VIIRS (10.0°C). These findings improve our understanding of WRF-CLMU behavior and highlight its potential applications for future high-resolution regional urban climate simulations.