Abstract

Context. COolfluid COrona uNstrUcTured (COCONUT) is a global coronal magnetohydrodynamic (MHD) model that was recently developed and will soon be integrated into the ESA Virtual Space Weather Modelling Centre (VSWMC). In order to achieve robustness and fast convergence to a steady state for numerical simulations with COCONUT, several assumptions and simplifications were made during its development, such as prescribing filtered photospheric magnetic maps to represent the magnetic field conditions in the lower corona. This filtering leads to smoothing and lower magnetic field values at the inner boundary (i.e. the solar surface), resulting in an unrealistically high plasma β (greater than 1 in a large portion of the domain). Aims. We aim to examine the effects of prescribing such filtered magnetograms in global coronal simulations and formulate a method for achieving more realistic plasma β values and improving the resolution of electromagnetic features without losing computational performance. Methods. We made use of the newly developed COCONUT solver to demonstrate the effects of the highly pre-processed magnetic maps set at the inner boundary and the resulting high plasma β on the features in the computational domain. Then, in our new approach, we shifted the inner boundary to 2 R⊙ from the original 1.01 R⊙ and preserved the prescribed highly filtered magnetic map. With the shifted boundary, the boundary density and pressure were also naturally adjusted to better represent the considered physical location. This effectively reduces the prescribed plasma β and leads to a more realistic setup. The method was applied on a magnetic dipole, a minimum (2008) and a maximum (2012) solar activity case, to demonstrate its effects. Results. The results obtained with the proposed approach show significant improvements in the resolved density and radial velocity profiles, and far more realistic values of the plasma β at the boundary and inside the computational domain. This is also demonstrated via synthetic white light imaging (WLI) and with the validation against tomography data. The computational performance comparison shows similar convergence to a limit residual on the same grid when compared to the original setup. Considering that the grid can be further coarsened with this new setup, as its capacity to resolve features or structures is superior, the operational performance can be additionally increased if needed. Conclusions. The newly developed method is thus deemed as a good potential replacement of the original setup for operational purposes, providing higher physical detail of the resolved profiles while preserving a good convergence and robustness of the solver.

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