Abstract
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.