Several recent studies have shown that much can be learned by comparing grid-point data from a data assimilation system with in-situ observations from field experiments. While the surface heterogeneity is acknowledged in these studies, they lack quantitative representations of the influence of heterogeneity on the near-surface meteorology and surface hydrologic and energy balance. Here, we use the Betts and Ball FIFE site-averaged data. Standard deviations of the site-average will provide an estimate of the FIFE site heterogeneity. Recently, the Mosaic Land-Surface Model (LSM) has been incorporated into the Goddard Earth Observing System (GEOS) Data Assimilation System (DAS). The Mosaic LSM computes the surface energy and hydrologic balance for nine distinct surface types at each grid-point. Each surface type is proportionally weighted to determine the mean grid point properties. Hence, we can compare modeled and observed gridpoint variability in addition to the mean properties. Also, assimilated data sets created with and without the LSM are compared. The results indicate the importance of including quantitative estimates of heterogeneity in the analysis of the land surface hydrology and energy balances in assimilation systems.