A major source of uncertainty in the aerosol forcing of climate is related to the vertical distribution of atmospheric aerosols with respect to clouds. Recent satellite observations reveal that aerosols are not limited to the boundary layer but rather are frequently observed above clouds, particularly in marine environments with low cloud cover. Compared to aerosols that occur beneath or in clouds, above-cloud aerosols (ACA), especially those that are light-absorbing, can intercept more solar radiation via multiple scattering between aerosol and cloud layers, which can result in an amplification of aerosol absorption and thus a smaller negative or even positive direct radiative forcing at the top-of-the-atmosphere. In this study, we perform the first evaluation of aerosol vertical distribution and absorption in the U.S. Department of Energy’s Energy Exascale Earth System Model (E3SM), with a focus on elevated aerosols in active ACA regions identified by satellite observations. We use satellite and ground-based observations from MODIS, CALIOP, and AERONET to compare modeled and observed aerosol optical depth (AOD), absorbing aerosol optical depth (AAOD), single-scattering albedo (SSA), aerosol vertical extinction profiles, and total and low cloud fractions. We find that the model captures the seasonal and spatial distributions of AOD well, while ground-based AERONET measurements of AOD and AAOD are generally higher than those simulated by E3SM. Model ACA consists predominantly of carbonaceous aerosols (black carbon and primary organic matter) from biomass burning and mineral dust from desert regions. ACA in E3SM peaks in summer and fall, when subtropical low cloud cover in the model is most prevalent. Overall, regions with active ACA in E3SM are consistent with those identified by observation. We compare speciated ACA occurrence frequency with CALIOP observations, and, using a radiative transfer model, we calculate the direct radiative impact due to bias attributed to the transport of elevated aerosols over the ACA regions identified.