  Computational Fluid Dynamics (CFD)-based global solar coronal simulations are
slowly making their way into the space weather modeling toolchains to replace
the semi-empirical methods such as the Wang-Sheeley-Arge (WSA) model. However,
since they are based on CFD, if the assumptions in them are too strong, these
codes might experience issues with convergence and unphysical solutions.
Particularly the magnetograms corresponding to solar maxima can pose problems
as they contain active regions with strong magnetic fields, resulting in large
gradients. Combined with the approximate way in which the inner boundary is
often treated, this can lead to non-physical features or even a complete
divergence of the simulation in these cases. Here, we show some of the possible
approaches to handle this inner boundary in our global coronal model COolfluid
COrona uNstrUcTured (COCONUT) in a way that improves both convergence and
accuracy. Since we know that prescribing the photospheric magnetic field for a
region that represents the lower corona is not entirely physical, first, we
look at the ways in which we can adjust the input magnetograms to remove the
highest magnitudes and gradients. Secondly, since in the default setup we also
assume a constant density, here we experiment with changing these values
locally and globally to see the effect on the results. We conclude, through
comparison with observations and convergence analysis, that modifying the
density locally in active regions is the best way to improve the performance
both in terms of convergence and physical accuracy from the tested approaches.
