Exploiting White-Light Observations to Improve Estimates of Magnetic Connectivity

Poirier, Nicolas; Rouillard, A. P.; Kouloumvakos, A.; Przybylak, Alexis; Fargette, N.; Pobeda, Raphaël; Réville, Victor; Pinto, Rui; Indurain, Mikel; Alexandre, M Tartakovsky

doi:10.3389/fspas.2021.684734

Cited by 19 publications

(24 citation statements)

References 40 publications

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“…As such, we trace the locus of maximal brightness at each longitude (see the dark dashed line in the middle panel of figure 2), hereafter called the Streamer-Maximum-Brightness (SMB) line. A good correlation has been found between the SMB line and the magnetic sector structure observed in situ at 1 AU (see Poirier et al 2021). Similarities between the brightest regions of the K-corona and the magnetic sector boundary have also been highlighted in past studies (Hansen et al 1974;Howard & Koomen 1974).…”

Section: White Light Synoptic Mapssupporting

confidence: 74%

“…For instance, the usual larger radial extent of streamers compared to pseudostreamers can help to discriminate between both (Wang et al 2007). For a start, we selected a height of 5.0 Rs, large enough to remove most of the pseudo-streamer signatures, while also keeping good image quality (further details can be found in Poirier et al 2021). The outermost boundary of the streamer belt is identified with a simple brightness threshold.…”

Section: White Light Synoptic Mapsmentioning

confidence: 99%

“…The global score is built so that a model having a good overall match with WL coronagraphic observations would still be penalized in case of local and large deviations from the SMB line. Further details on the derivation of this global score can be found in Poirier et al (2021) where the following formula has been retained:…”

Section: Streamer Beltmentioning

confidence: 99%

“…As a consequence, the reliability of this metric is uncertain for highly structured coronal configurations typically observed during periods of high solar activity. Limitations of this WL metric are discussed in further detail in Poirier et al (2021). Future improvements are also discussed which may increase the reliability of this metric for more complex configurations.…”

Section: Streamer Beltmentioning

confidence: 99%

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Constraining Global Coronal Models with Multiple Independent Observables

Badman,

Brooks,

Poirier

et al. 2022

Preprint

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Global coronal models seek to produce an accurate physical representation of the Sun's atmosphere which 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 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 1AU 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 Magnetohydrodynamics 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 they include addresses 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.

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Section: White Light Synoptic Mapssupporting

confidence: 74%

Section: White Light Synoptic Mapsmentioning

confidence: 99%

Section: Streamer Beltmentioning

confidence: 99%

Section: Streamer Beltmentioning

confidence: 99%

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Constraining Global Coronal Models with Multiple Independent Observables

Badman,

Brooks,

Poirier

et al. 2022

Preprint

Self Cite

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“…In fact, both other codes and data suggests that the PFSS can either overestimate or underestimate the magnetic field at 0.1 AU depending on the parameters chosen, which shows that COCONUT is yielding expected results (van der Holst et al 2010;Mc-Gregor et al 2011;Réville et al 2022). Unfortunately, we don't have observations data for this date to discuss which code is better, but in future studies we can select other events to use PSP (Badman et al 2022) or SoHO/LASCO white-light images (Poirier et al 2021).…”

Section: Model Validation With Observationsmentioning

confidence: 91%

COCONUT, a novel fast-converging MHD model for solar corona simulations: I. Benchmarking and optimization of polytropic solutions

Perri,

Leitner,

Brchnelova

et al. 2022

Preprint

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We present a novel global 3-D coronal MHD model called COCONUT, polytropic in its first stage and based on a time-implicit backward Euler scheme. Our model boosts run-time performance in comparison with contemporary MHD-solvers based on explicit schemes, which is particularly important when later employed in an operational setting for space weather forecasting. It is data-driven in the sense that we use synoptic maps as inner boundary input for our potential field initialization as well as an inner boundary condition in the further MHD time evolution. The coronal model is developed as part of the EUropean Heliospheric FORecasting Information Asset (EUHFORIA) and will replace the currently employed, more simplistic, empirical Wang-Sheeley-Arge (WSA) model. At 21.5 R where the solar wind is already supersonic, it is coupled to EUHFORIA's heliospheric model. We validate and benchmark our coronal simulation results with the explicit-scheme Wind-Predict model and find good agreement for idealized limit cases as well as real magnetograms, while obtaining a computational time reduction of up to a factor 3 for simple idealized cases, and up to 35 for realistic configurations, and we demonstrate that the time gained increases with the spatial resolution of the input synoptic map. We also use observations to constrain the model and show that it recovers relevant features such as the position and shape of the streamers (by comparison with eclipse white-light images), the coronal holes (by comparison with EUV images) and the current sheet (by comparison with WSA model at 0.1 AU).

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