Wildfires are becoming more prevalent in the southeastern United States. Wildfires emit light absorbing organic aerosols such as black carbon and dark brown carbon (tar balls) that influence regional air quality and radiative forcing. Recent experimental work has identified dark brown carbon as a potentially significant source of warming in the atmosphere. However, dark brown carbon is not typically included in air quality and climate models. We added dark brown carbon from wildfires as a species in the Weather Research and Forecasting modeling system coupled with chemistry (WRF-Chem) version 4.2 with the Quick-Fire Emissions Database (QFED). The model simulations were run over the southeastern United States from June 21^st to June 30^th 2013 in conjunction with in-situ measurements of aerosol extinction from the Southeast Nexus (SENEX) aircraft campaign and aerosol optical depth (AOD) measurements from the ground-based remote sensing Aerosol Robotic Network (AERONET). The impacts of imaginary refractive index, aerosol mixing, and Mie method were investigated with an offline radiation model for computationally efficient evaluation. Dark brown carbon was found to increase absorbing aerosol optical depth (AAOD) by up to 5.2 % in the simulation time and region. We derived a linear equation to estimate the correlation between modeled AAOD and columnar dark brown carbon (AAOD = 0.0023[D-BrC] + 0.0007) with core-shell considerations. Core-shell aerosol mixing and explicit Mie computation enhanced increases in AAOD from dark brown carbon at AERONET sites (up to 6.42 %). These results indicate that models omitting dark brown carbon may underestimate aerosol absorption in wildfire-influenced regions, and that including it, along with a realistic mixing state and Mie treatment, is important for estimating radiative forcing as wildfire activity increases.