Constraining Global Coronal Models with Multiple Independent Observables

Abstract

Global coronal models seek to produce an accurate physical representation of the Sun’s atmosphere that can be used, for example, to drive space-weather models. Assessing their accuracy is a complex task, and there are multiple observational pathways to provide constraints and tune model parameters. Here, we combine several such independent constraints, defining a model-agnostic framework for standardized comparison. We require models to predict the distribution of coronal holes at the photosphere, and neutral line topology at the model’s outer boundary. We compare these predictions to extreme-ultraviolet (EUV) observations of coronal hole locations, white-light Carrington maps of the streamer belt, and the magnetic sector structure measured in situ by Parker Solar Probe and 1 au spacecraft. We study these metrics for potential field source surface (PFSS) models as a function of source surface height and magnetogram choice, as well as comparing to the more physical Wang–Sheeley–Arge (WSA) and the Magnetohydrodynamic Algorithm outside a Sphere (MAS) models. We find that simultaneous optimization of PFSS models to all three metrics is not currently possible, implying a trade-off between the quality of representation of coronal holes and streamer belt topology. WSA and MAS results show the additional physics that they include address this by flattening the streamer belt while maintaining coronal hole sizes, with MAS also improving coronal hole representation relative to WSA. We conclude that this framework is highly useful for inter- and intra-model comparisons. Integral to the framework is the standardization of observables required of each model, evaluating different model aspects.

Modeling the Solar Wind during Different Phases of the Last Solar Cycle

“…It is important to point out that we limit the model validation to the in situ data comparison. Other solar corona observations, for example, the white light images (Badman et al 2022), are not included in the current study.…”

COCONUT, a Novel Fast-converging MHD Model for Solar Corona Simulations. II. Assessing the Impact of the Input Magnetic Map on Space-weather Forecasting at Minimum of Activity

“…The second physical quantity we use for comparison is the EUV emission at 195 Å, which is the wavelength recommended to automatically extract coronal hole boundaries (Badman et al 2022;Wagner et al 2022). Coronal holes are dimmings in the EUV emission, which correspond to regions of open magnetic field lines associated with cooler plasma (Cranmer 2009).…”

COCONUT, a Novel Fast-converging MHD Model for Solar Corona Simulations. III. Impact of the Preprocessing of the Magnetic Map on the Modeling of the Solar Cycle Activity and Comparison with Observations

“…(e.g., Keppens & Goedbloed 1999). As our COCONUT global coronal model is being further developed and more physics is added, such as terms for heating and loss (thermal conduction and radiation), we have opted for more general and broader diagnostics that can be used beyond MHD models, such as in the frameworks defined by Wagner et al (2022) and Badman et al (2022). In our future work, we plan to use more sophisticated approaches, one of them being the ISWAT initiative (Reiss et al 2022)with the aim of unification of the validation of ambient solar wind models.…”

“…Inspired by the Solar Orbiter and Parker Solar Probe missions, they proposed a metric to rank coronal models according to their relevance to WL images. Following this research, Badman et al (2022) defined a "model-agnostic" framework for standardized comparison with observations and tested it on Potential Field Source Surface (PFSS), WSA, and MAS models. They focused on the coronal hole distribution at the photospheric level, comparing it with EUV observations, and on the neutral line at the outer boundary, comparing it with WL Carrington maps of the streamer belt and magnetic sector structure measured in situ by Parker Solar Probe.…”