The human conversion of the land surface over the last few centuries has resulted in a significant modification of its biophysical properties (Ramankutty and Foley 1999). Modification of land cover, its spatial heterogeneity as well as its mean characteristics, drives changes in the land-atmosphere fluxes of heat, moisture, and momentum. These changes in turn impact weather and climate through influences on atmospheric dynamics, thermodynamics, convection, clouds, and rainfall (see Pielke 2001 for a review). A number of recent studies have suggested that impacts of land cover change on large-scale climate could be comparable to those associated with changing atmospheric composition. Links between the patterns of land cover change, the processes driving it, and its impacts on the weather and climate are particularly strong at scales much finer than global. For example, studies have begun to demonstrate the significant influence of anthropogenic surface perturbations on mesoscale atmospheric processes (e.g., see Weaver and Avissar 2001). Quantifying the types of land cover change and the subsequent responses of the coupled land-atmosphere system that can occur at regional and local scales is critical, as these are the scales of ecosystems and human communities. Many important issues are not yet well understood, however, and attacking this problem is the overarching theme of the work described here. Our particular focus is land cover change in New Jersey and surrounding regions during the last century. In the northeastern U.S. in general, extensive urban and industrial development, along with the displacement of agriculture, has produced dramatic changes in land cover. We wish to understand in what ways, and to what extent, these land-surface changes have altered the climate of this region. This question is relevant from a number of perspectives. For example, separating the effects of land cover change will assist in distinguishing the regional fingerprints of a possible global climate change signal. In addition, landscape change driven by population growth and economic development is expected to continue, and even accelerate, into the future. An evaluation of how historical land cover change may have modified weather and climate is one prerequisite for understanding and predicting the broader impacts of future changes. Specifically, we are attempting to answer the following questions: How did 1880s land cover in and around New Jersey differ from that of the present day? What are the impacts of these differences on regional weather patterns and climate? In particular, what are the differences in temperature, evapotranspiration, atmospheric boundary layer structure, atmospheric dynamics, clouds, and precipitation, including differences in the spatial and temporal variability of these quantities, which can be attributed to the land cover changes? Can we use these insights to help predict future climate impacts arising from expected future land use/land cover changes? In particular, what is the range of impacts on meteorological variables implied by reasonable scenarios of future land cover? What further consequences, e.g., on ecosystem processes, agriculture, water resources, energy supply and demand, and public health, might we expect as a result? We have selected New Jersey as the primary domain of interest because it is, to our knowledge, the only state in the country where a spatially accurate dataset of documented 19th-century land cover is available at a resolution comparable to that of satellite imagery. Our main tools for investigating the scientific questions posed above are (a) this historical dataset, (b) the USGS National Land Cover Dataset (NLCD), based on Landsat Thematic Mapper imagery, and (c) a state-of-the-art mesoscale numerical model, the Regional Atmospheric Modeling System (RAMS). Our strategy is to run RAMS at high resolution, forced at the lower boundary with these representations of historical and present-day land cover (and, eventually, scenarios of future land cover), and to quantify the differences between these experiments.