The sensitivity of the WRF modeling system to different model realizations was tested by creating an ensemble of runs utilizing different ABL schemes, urban canopy models (UCMs), and a new subroutine that was created to reduce the overestimation of urban land cover. Urban land cover is just one example of the input data used by UCMs in WRF. These input data can be improved by integrating new and updated databases describing urban areas. Updates to the urban land cover parameter improved the modeled sensible and latent heat flux by as much as 30%; however, the bias and spread of the errors in other meteorological variables, such as ABL height, wind speed, and wind direction, were dominated by the parameterization schemes chosen for each model run. While a more accurate representation of urban parameters will not always produce smaller forecast errors, adding more accurate and heterogeneous parameter values will allow us to identify what parameterizations are deficient in the UCM and in the WRF modeling system. By using the observations made available through the INFLUX project, the assessment of model transport errors will lead to a more accurate atmospheric inversion that will be produced by the INFLUX project and a greater understanding of sources of modeled atmospheric transport errors over urban environments.