Consisting of charged particles originating from the Sun, the solar wind carries the Sun’s energy and magnetic field outward through interplanetary space. The solar wind is the predominant source of space weather events, and modeling the solar wind propagation to Earth is a critical component of space weather research. Solar wind models are typically separated into coronal and heliospheric parts to account for the different physical processes and scales characterizing each region. Coronal models are often coupled with heliospheric models to propagate the solar wind out to Earth’s orbit and beyond. The Wang-Sheeley-Arge (WSA) model is a semi-empirical coronal model consisting of a potential field source surface model and a current sheet model that takes synoptic magnetograms as input to estimate the magnetic field and solar wind speed at any distance above the coronal region. The current version of the WSA model takes the Air Force Data Assimilative Photospheric Flux Transport (ADAPT) model as input to provide improved time-varying solutions for the ambient solar wind structure. When heliospheric MHD models are coupled with the WSA model, density and temperature at the inner boundary are treated as free parameters that are tuned to optimal values. For example, the WSA-ENLIL model prescribes density and temperature assuming momentum flux and thermal pressure balance across the inner boundary of the ENLIL heliospheric MHD model. We consider an alternative approach of prescribing density and temperature using empirical correlations derived from Ulysses and OMNI data. We use our own modeling software (Multi-scale Fluid-kinetic Simulation Suite) to drive a heliospheric MHD model with ADAPT-WSA input. The modeling results using the two different approaches of density and temperature prescription suggest that the use of empirical correlations may be a more straightforward, consistent method.