Landscape heterogeneity that causes surface flux variability plays a very important role in triggering mesoscale atmospheric circulations and convective weather processes. In most mesoscale numerical models, however, subgrid-scale heterogeneity is somewhat smoothed or not adequately accounted for, leading to artificial changes in heterogeneity patterns (e.g., patterns of land cover, land use, terrain, and soil types and soil moisture). At the domain-wide scale, the combination of losses in subgrid-scale heterogeneity from many adjacent grids may artificially produce larger-scale, more homogeneous landscapes. Therefore, increased grid spacing in models may result in increased losses in landscape heterogeneity. Using the Weather Research and Forecasting model in this paper, we design a number of experiments to examine the effects of such artificial changes in heterogeneity patterns on numerical simulations of surface flux exchanges, near-surface meteorological fields, atmospheric planetary boundary layer (PBL) processes, mesoscale circulations, and mesoscale fluxes. Our results indicate that the increased heterogeneity losses in the model lead to substantial, nonlinear changes in temporal evaluations and spatial patterns of PBL dynamic and thermodynamic processes. The decreased heterogeneity favor developments of more organized mesoscale circulations, leading to enhanced mesoscale fluxes and, in turn, the vertical transport of heat and moisture. This effect is more pronounced in the areas with greater surface heterogeneity. Since more homogeneous land-surface characteristics are created in regional models with greater surface grid scales, these artificial mesoscale fluxes may have significant impacts on simulations of larger-scale atmospheric processes.