Modeling Land Surface Processes and Heavy Rainfall in Urban Environments: Sensitivity to Urban Surface Representations

High-resolution simulations with the Weather Research and Forecasting Model (WRF) are used in conjunction with observational analyses to investigate land surface processes and heavy rainfall over the Baltimore-Washington metropolitan area. Analyses focus on a 6-day period, 21-26 July 2008, which includes a major convective rain event (23-24 July), a prestorm period (21-22 July), and a dry-down period (25-26 July). The performance of WRF in capturing land-atmosphere interactions, the bulk structure of the atmospheric boundary layer, and the rainfall pattern in urban environments is explored. Results indicate that WRF captures the incoming radiative fluxes and surface meteorological conditions. Mean profiles of potential temperature and humidity in the atmosphere are also relatively well reproduced, both preceding and following the heavy rainfall period. However, wind features in the lower atmosphere, including low-level jets, are not accurately reproduced by WRF. The biases in the wind fields play a central role in determining errors in WRF-simulated rainfall fields. The study also investigates the sensitivity of WRF simulations to different urban surface representations. It is found that urban surface representations have a significant impact on the surface energy balance and the rainfall distribution. As the impervious fraction increases, the sensible heat flux and the ground heat flux increase, while the latent heat flux decreases. The impact of urban surface representations on precipitation is as significant as that of microphysical parameterizations. The fact that changing urban surface representations can significantly alter the rainfall field suggests that urbanization plays an important role in modifying the regional precipitation pattern.