Abstract

The current Weather Research and Forecasting (WRF)-Noah modeling framework considers only the dominant land cover type within each grid cell, which here is referred to as the “dominant” approach. In order to assess the impact of subgrid-scale variability in land cover composition, a mosaic/tiling... Show moreThe current Weather Research and Forecasting (WRF)-Noah modeling framework considers only the dominant land cover type within each grid cell, which here is referred to as the “dominant” approach. In order to assess the impact of subgrid-scale variability in land cover composition, a mosaic/tiling approach (hereafter the “mosaic” approach) is implemented into the coupled WRF-Noah modeling system. In the mosaic approach, a certain number (N) of tiles, each representing a land cover category, is considered within each grid cell. WRF simulations of a clear sky day and a rainfall period over a heterogeneous urban/suburban setting show that the two approaches generate differences in the surface energy balance, land surface temperature, near-surface states, boundary layer growth, as well as rainfall distribution. Evaluation against a variety of observational data (including surface flux measurements, the MODIS land surface temperature product, and radar rainfall estimates) indicates that, compared to the dominant approach, the mosaic approach has a better performance. In addition, WRF-simulated results with the mosaic approach are less sensitive to the spatial resolution of the grid: Larger differences are observed in simulations of different resolutions with the dominant approach. The effect of increasing the number of tiles (N) on the WRF-simulated results is also examined. When N increases from 1 (i.e., the dominant approach) to 15, changes in the ground heat flux, sensible heat flux, surface temperature, and 2 m air temperature are more significant during nighttime. Changes in the 2 m specific humidity are more significant during daytime, and changes in the boundary layer height are most prominent during the morning and afternoon transitional periods. Show less