| description abstract | A 6.25-km resolution dataset of meteorology, vegetation type, and soil type for a domain covering a typical global climate model grid cell is used to drive a land surface physics model for a period of 6 months. Additional simulations are performed driving the land surface physics model by spatially averaged meteorology, spatially averaged vegetation characteristics, spatially averaged soil properties, and spatially averaged meteorology, vegetation characteristics, and soil properties. By comparing the simulated water balance for the whole domain for each simulation, the relative influence of subgrid variability in meteorology, vegetation, and soil are assessed. Subgrid variability in summertime precipitation is found to have the largest effect on the surface hydrology, with a nearly twofold increase on surface runoff and a 15% increase in evapotranspiration. Subgrid variations in vegetation and soil properties also increase surface runoff and reduce evapotranspiration, so that surface runoff is 2.75 times as great with subgrid variability than without and evapotranspiration is 19% higher with subgrid variability than without. | |
