Topography has major control on land surface processes through its influence on atmospheric forcing, soil and vegetation properties, network topology and drainage area. Consequently, accurate climate and land surface simulations in mountainous regions cannot be achieved without considering the effects of topographic spatial heterogeneity. To test a computationally less expensive hyper-resolution land surface modeling approach, we developed topography-based landunits within a hierarchical subgrid spatial structure to improve representation of land surface processes in the ACME Land Model (ALM) with minimal increase in computational demand, while improving the ability to capture the spatial heterogeneity of atmospheric forcing and land cover influenced by topography. This study focuses on evaluation of the impacts of the new spatial structures on modeling land surface processes. As a first step, we compare ALM simulations with and without subgrid topography and driven by grid cell mean atmospheric forcing to isolate the impacts of the subgrid topography on the simulated land surface states and fluxes. Recognizing that subgrid topography also has important effects on atmospheric processes that control temperature, radiation, and precipitation, methods are being developed to downscale atmospheric forcings. Hence in the second step, the impacts of the subgrid topographic structure on land surface modeling will be evaluated by including spatial downscaling of the atmospheric forcings. Preliminary results on the atmospheric downscaling and the effects of the new spatial structures on the ALM simulations will be presented.