Vegetation and soil properties at the land surface exert significant influence over short-term weather forecasts in numerical weather prediction (NWP) models. The Coupled Ocean Atmosphere Mesoscale Prediction System (COAMPS) model derives the necessary land surface properties from the USGS 1-km global land-use/land-cover (LULC) database, which is based on historical AVHRR data. A methodology has been developed to incorporate the LULC and vegetation information, derived from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) sensors, into the COAMPS model, running on nested domains – centered over the Mississippi Gulf Coast. The MODIS LULC data exhibits greater variability over the land areas of southeastern United States compared to the historical AVHRR data. Hence, it is expected that the use of the MODIS LULC data in the COAMPS model will result in realistic estimates of the energy and moisture fluxes across the land-atmosphere interface. The COAMPS model software has been modified to utilize the MODIS LULC data set. Methodology developed to utilize the MODIS data and the results from the model runs using the two different LULC datasets will be presented during the conference. The influence of the MODIS derived vegetation data on the prediction of sea breeze along the Mississippi Gulf Coast is being investigated and the results will also be discussed.