Heterogeneous reactions occurring at the surface of atmospheric aerosol particles regulate the production and lifetime of a wide array of atmospheric gases. Aerosol surface area plays a critical role in setting the rate of heterogeneous reactions in atmospheric chemistry. Despite the central role for aerosol surface area, there are few assessments of the accuracy of aerosol surface area concentrations in regional and global models. In this study, we compare aerosol surface area concentrations in the EPA’s CMAQ (Community Multiscale Air Quality) model with commensurate observations from the 2011 NASA flight-based DISCOVER-AQ (Deriving Information on Surface Conditions from COlumn and VERtically Resolved Observations Relevant to Air Quality) campaign. The study region for the 2011 DISCOVER-AQ campaign focused primarily on the Baltimore and Washington, DC region. Dry aerosol surface area was measured aboard the NASA P-3B aircraft using a combination of a Scanning Mobility Particle Sizer (SMPS), Aerodynamic Particle Sizer (APS), and Ultra-High Sensitivity Aerosol Spectrometer (UHSAS). In this study, we focus on the continuous 1s UHSAS measurements in size range of 60-1000nm, as it captures the majority of the dry surface area distribution. Over the course of 13 flight campaigns, we show strong agreement between measured and modeled aerosol number concentration (CMAQ Number/UHSAS Number= 0.88). In contrast, the total surface area showed a larger discrepancy (CMAQ surface area/UHSAS surface area = 0.44). We hypothesize that the emissions and chemistry in CMAQ relating to the production and loss of each moment play a large part in the model/measurement discrepancy. Despite the disagreement, this analysis suggests that modeled aerosol surface area is accurate to within a factor of two, highlighting that uncertainty in the rate of heterogeneous reactions is largely driven by uncertainty in the reactive uptake coefficients. We would like to thank the DISCOVER-AQ NASA Langley Aerosol Research Group Experiment (LARGE) research team, including Richard Moore, Bruce Anderson, Andreas Beyersdorf, Luke Ziemba, Lee Thornhill, and Edward Winstead for the use of their data in this study.