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The effects of small-scale heterogeneity in land-surface characteristics on the large-scale fluxes of water and energy in the land-atmosphere system have become a central focus of many of the climatology research experiments. The acquisition of high-resolution land-surface data through remote sensing and intensive land-climatology field experiments(like HAPEX and EIFE) has provided data to investigate the interactions between microscale land-atmosphere interactions and macroscale models. One essential research question is how to account for the small-scale heterogeneities and whether `effective' parameters can be used in the macroscale models. To address this question ofscaling, three modeling experiments were performed and are reviewed in the paper. The first is concerned with the land-surface hydrology during rain events and between rain events. The second experiment applies the Simple Biosphere Model (SiB) to a heterogeneous domain and the spatial and temporal latent beat flux is analyzed. The third experiment uses thermatic mapper (TM) data to look at the scaling of the normalized vegetation index (NDVI), latent heat flux, and sensible heat flux through either scaling of the TM-derived fields using the TM data or the fields derived from aggregated TM data.In all three experiments it was found that the surface fluxes and land characteristics can be sealed, and that macroscale models based on elective parameters are sufficient to account for the small-scale heterogeneities investigated. The paper also suggests that the scale at which a macroscale model becomes valid, the representative elementary scale (REA), is on the order 1.5-3 correlation lengths, which for land processes investigated appears to be about 1000-1500 m. At scales less than the REA scale, exact patterns of subgrid heterogeneities are needed for accurate small-scale modeling.