Validation scheme for solar coronal models -- constraints from multi-perspective observations in EUV and white-light

TL;DR

This paper introduces a validation scheme for solar coronal magnetic field models, utilizing multi-perspective EUV and white-light observations to objectively assess model accuracy and reliability.

Contribution

The paper develops a validation framework that combines empirical visual classification with topology metrics, applicable to any coronal model producing magnetic field line topology.

Findings

Validation scheme effectively assesses model quality.

Application to EUHFORIA model shows optimal parameter set.

Combined approach improves objectivity in model validation.

Abstract

Context: In this paper we present a validation scheme to investigate the quality of coronal magnetic field models, which is based upon comparisons with observational data from multiple sources. Aims: Many of these coronal models may use a range of initial parameters that produce a large number of physically reasonable field configurations. However, that does not mean that these results are reliable and comply with the observations. With an appropriate validation scheme the quality of a coronal model can be assessed. Methods: The validation scheme is developed on the example of the EUropean Heliospheric FORecasting Information Asset (EUHFORIA) coronal model. For observational comparison we use EUV and white-light data to detect coronal features on the surface (open magnetic field areas) and off-limb (streamer and loop) structures from multiple perspectives (Earth view and the Solar Terrestrial Relations Observatory - STEREO). The validation scheme can be applied to any coronal model that produces magnetic field line topology. Results: We show its applicability by using that validation scheme on a large set of model configurations, which can be efficiently reduced to an ideal set of parameters that matches best with observational data. Conclusions: We conclude that by using a combined empirical visual classification with a mathematical scheme of topology metrics a very efficient and rather objective quality assessment for coronal models can be performed.