Quantifying errors in 3D CME parameters derived from synthetic data using white-light reconstruction techniques

Verbeke, C.; Mays, M. L.; Kay, C.; Riley, Pete; Palmerio, Erika; Dumbović, Mateja; Mierla, M.; Scolini, Camilla; Temmer, Manuela; Paouris, Evangelos; Balmaceda, L. A.; Cremades, H.; Hinterreiter, Jürgen

doi:10.1016/j.asr.2022.08.056

Cited by 33 publications

(23 citation statements)

References 56 publications

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“…(2009), and Verbeke et al. (2023), which we will refer to as V23, P19, and T09, respectively. V23 determined the errors in GCS reconstructions using synthetic white‐light events, which have known values and for which a perfect reconstruction is possible.…”

Section: Variation Within Multi‐cat Eventsmentioning

confidence: 99%

Collection, Collation, and Comparison of 3D Coronal CME Reconstructions

Kay,

Palmerio

2024

Space Weather

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Predicting the impacts of coronal mass ejections (CMEs) is a major focus of current space weather forecasting efforts. Typically, CME properties are reconstructed from stereoscopic coronal images and then used to forward model a CME's interplanetary evolution. Knowing the uncertainty in the coronal reconstructions is then a critical factor in determining the uncertainty of any predictions. A growing number of catalogs of coronal CME reconstructions exist, but no extensive comparison between these catalogs has yet been performed. Here we develop a Living List of Attributes Measured in Any Coronal Reconstruction (LLAMACoRe), an online collection of individual catalogs, which we intend to continually update. In this first version, we use results from 24 different catalogs with 3D reconstructions using Solar Terrestrial Relations Observatory observations between 2007 and 2014. We have collated the individual catalogs, determining which reconstructions correspond to the same events. LLAMACoRe contains 2,954 reconstructions for 1,862 CMEs. Of these, 511 CMEs contain multiple reconstructions from different catalogs. Using the best‐constrained values for each CME, we find that the combined catalog reproduces the generally known solar cycle trends. We determine the typical difference we would expect between two independent reconstructions of the same event and find values of 4.0° in the latitude, 8.0° in the longitude, 24.0° in the tilt, 9.3° in the angular width, 0.1 in the shape parameter κ, 115 km/s in the velocity, and 2.5 × 1015 g in the mass. These remain the most probable values over the solar cycle, though we find more extreme outliers in the deviation toward solar maximum.

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Section: Variation Within Multi‐cat Eventsmentioning

confidence: 99%

Collection, Collation, and Comparison of 3D Coronal CME Reconstructions

Kay,

Palmerio

2024

Space Weather

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“…While difficult to define with great precision, these two values can be fairly easily estimated from extreme ultra‐violet (EUV) images of the solar disk. We acknowledge that defining these values may be significantly subject to user/forecaster interpretation, much like reconstructing CME positions from coronagraph images (e.g., Verbeke et al., 2022).…”

Section: Application To 1 Au Hss Forecastsmentioning

confidence: 99%

“…We acknowledge that defining these values may be significantly subject to user/forecaster interpretation, much like reconstructing CME positions from coronagraph images (e.g., Verbeke et al, 2022).…”

Section: Application To 1 Au Hss Forecastsmentioning

confidence: 99%

An Efficient, Time‐Dependent High Speed Stream Model and Application to Solar Wind Forecasts

et al. 2023

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A continuous stream of plasma blows out from the solar atmosphere, spreading out into interplanetary space. This so-called solar wind is not uniform, but rather contains distinct regions of fast (≳600 km/s) and slow (300-400 km/s) plasma flows. The fast solar wind is known to originate along the open magnetic field lines emanating from coronal holes (CHs; e.g., Cranmer, 2009) but there is less consensus on the source of the slow wind (see Cranmer et al., 2017, for a review on the origins of the ambient solar wind). Possible sources of the slow wind that have been proposed in the literature include helmet streamers (e.g.,

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“…In addition to the limitations imposed by the sensitivity of measurements, it is prone to errors for reasons ranging from human subjectiveness to relative locations of the vantage points. To quantify these errors, Thernisien et al (2009); Verbeke et al (2022) examined a large number of synthetic CMEs of different kinds observed using different numbers and configurations of spacecraft. They found that adding observations from a third or more vantage points do not reduce the errors on the model parameters significantly.…”

Section: Estimation Of Geometrical Parametersmentioning

confidence: 99%

“…To overcome this limitation, we generated 10,000 realizations of GCS model parameters from independent Gaussian distributions for each of the parameters. The mean of these distributions was set to the fitted values and the standard deviation to the uncertainty reported in Verbeke et al (2022). L geo was computed for each of these realizations.…”

Section: Estimation Of Geometrical Parametersmentioning

confidence: 99%

Deciphering Faint Gyrosynchrotron Emission from Coronal Mass Ejection using Spectro-polarimetric Radio Imaging

Kansabanik¹,

Mondal²,

Oberoi³

2023

Preprint

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Measurements of the plasma parameters of coronal mass ejections (CMEs), particularly the magnetic field and non-thermal electron population entrained in the CME plasma, are crucial to understand their propagation, evolution, and geo-effectiveness. Spectral modeling of gyrosynchrotron (GS) emission from CME plasma has been regarded as one of the most promising remote sensing technique for estimating spatially resolved CME plasma parameters. Imaging the very low flux density CME GS emission in close proximity to the Sun with orders of magnitude higher flux density, however, has proven to be rather challenging. This challenge has only recently been met using the high dynamic range imaging capability of the Murchison Widefield Array (MWA). Although routine detection of GS is now within reach, the challenge has shifted to constraining the large number of free parameters in GS models, a few of which are degenerate, using the limited number of spectral points at which the observations are typically available. These degeneracies can be broken using polarimetric imaging. For the first time, we demonstrate this using our recently developed capability of high fidelity polarimetric imaging on the data from the MWA. We show that, in addition to breaking the degeneracies, spectropolarimetric spectroscopic imaging also yields tighter constraints on the plasma parameters of key interest than possible with total intensity spectroscopic imaging alone.

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Quantifying errors in 3D CME parameters derived from synthetic data using white-light reconstruction techniques

Cited by 33 publications

References 56 publications

Collection, Collation, and Comparison of 3D Coronal CME Reconstructions

Collection, Collation, and Comparison of 3D Coronal CME Reconstructions

An Efficient, Time‐Dependent High Speed Stream Model and Application to Solar Wind Forecasts

Deciphering Faint Gyrosynchrotron Emission from Coronal Mass Ejection using Spectro-polarimetric Radio Imaging

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