In this study GOES-derived skin temperature, insolation, surface albedo, cloud albedo, and cloud top temperatures have been utilized to improve the predictions of the MM5/CMAQ air quality modeling system for a 10 day period during a case study in the summer of 2000. First, GOES-derived products are assimilated in MM5 to recover moisture availability and heat capacity over the south-central U.S. Then the resulting meteorological predictions, together with GOES observed cloud information are used to drive CMAQ. Since in air quality studies the ultimate objective is the accuracy of the air quality predictions, the results are evaluated against observations and compared with the control simulations to assess the impact of assimilation on the model predictions. The impact of the assimilation on the predictions of planetary boundary-layer height, air temperature, and ground temperature also are evaluated.