As is typical in the Northern Hemisphere spring, during 20 April to 21 May 2003, significant biomass burning smoke from Central America was transported to the southeastern United States (SEUS). A coupled aerosol, radiation, and meteorology model that is built upon the heritage of the Regional Atmospheric Modeling System (RAMS), having newly developed capabilities of Assimilation and Radiation Online Modeling of Aerosols (AROMA) algorithm, was used to simulate the smoke transport and quantify the smoke radiative impacts on surface energetics, boundary layer, and other atmospheric processes. This paper, the first of a two-part series, describes the model and examines the ability of RAMS-AROMA to simulate the smoke transport. Because biomass-burning fire activities have distinct diurnal variations, the FLAMBE hourly smoke emission inventory that is derived from the geostationary satellite (GOES) fire products was assimilated into the model. In the "top-down" analysis, ground-based observations were used to evaluate the model performance, and the comparisons with model-simulated results were used to estimate emission uncertainties. Qualitatively, a 30-day simulation of smoke spatial distribution as well as the timing and location of the smoke fronts are consistent with those identified from the PM2.5 observation network, local air quality reports, and the measurements of aerosol optical thickness (AOT) and aerosol vertical profiles from the Southern Great Plains (SGP) Atmospheric Radiation Measurements (ARM) site in Oklahoma. Quantitatively, the model-simulated daily mean near-surface dry smoke mass correlates well with PM2.5 mass at 34 locations in Texas and with the total carbon mass and nonsoil potassium mass (KNON) at three IMPROVE sites along the smoke pathway (with linear correlation coefficients R = 0.77, 0.74, and 0.69 at the significance level larger than 0.99, respectively). The top-down sensitivity analysis indicates that the total smoke particle emission during the study period is about 1.3 ¿ 0.2 Tg. The results further indicate that the simulation with a daily smoke emission inventory provides a slightly better correlation with measurements in the downwind region on daily scales but gives an unrealistic diurnal variation of AOT in the smoke source region. This study suggests that the assimilation of emission inventories from geostationary satellites is superior to that of polar orbiting satellites and has important implications for the modeling of air quality in areas influenced by fire-related pollutants from distant sources.