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Global coronal models seek to produce an accurate physical representation ofthe Sun's atmosphere which can be used, for example, to drive space weathermodels. Assessing their accuracy is a complex task and there are multipleobservational pathways to provide constraints and tune model parameters. Here,we combine several such independent constraints, defining a model-agnosticframework for standardized comparison. We require models to predict thedistribution of coronal holes at the photosphere, and neutral line topology atthe model outer boundary. We compare these predictions to extreme ultraviolet(EUV) observations of coronal hole locations, white-light Carrington maps ofthe streamer belt and the magnetic sector structure measured \textit{in situ}by Parker Solar Probe and 1AU spacecraft. We study these metrics for PotentialField Source Surface (PFSS) models as a function of source surface height andmagnetogram choice, as well as comparing to the more physical Wang-Sheeley-Arge(WSA) and the Magnetohydrodynamics Algorithm outside a Sphere (MAS) models. Wefind that simultaneous optimization of PFSS models to all three metrics is notcurrently possible, implying a trade-off between the quality of representationof coronal holes and streamer belt topology. WSA and MAS results show theadditional physics they include addresses this by flattening the streamer beltwhile maintaining coronal hole sizes, with MAS also improving coronal holerepresentation relative to WSA. We conclude that this framework is highlyuseful for inter- and intra-model comparisons. Integral to the framework is thestandardization of observables required of each model, evaluating differentmodel aspects.

Constraining Global Coronal Models with Multiple Independent Observables