Concentration of Air Quality Models (CMAQ) has a deep connection with emissions and wind fields. In particular the wind field is highly affected by local topography and plays an important role in transport and dispersion of contaminants from the pollution sources. The purpose of this study is to examine the impact of interpolation on Air quality model. This study was designed to evaluate enhancement of MM5 and CMAQ predictions by using Four Dimensional Data Assimilation (FDDA), the SONDE data and the national meteorological station and the MODerate resolution Imaging Spectroradiometer (MODIS). The alternative meteorological fields predicted with and without MODIS data were used to simulate spatial and temporal variations of ozone in combined with CMAQ on June 2006. The result of this study indicated that data assimilation using MODIS data provided an attractive method for generating realistic meteorological fields and dispersion fields of ozone in the Korea peninsular, because MODIS data in 10 km domain are grid horizontally and vertically. In order to ensure the success of Air quality model, it is necessary to FDDA using MODIS data.