Graduated Cylindrical Shell (GCS) model is a widely used tool to determine direction, kinematic and orientation properties of Coronal Mass Ejections (CME) using multi-viewpoint observations from SOHO and STEREO A&B coronagraphs. In this study, we estimate the subjective uncertainties typically seen while deriving these CME properties by comparing the GCS model results reported in multiple studies and catalogs for 56 CMEs. We find that the GCS estimates of latitude, longitude, and tilt show an average uncertainty of 5.7, 11.2, and 24.7 degrees with standard deviation of 5.5, 12.7, and 19.7 degrees respectively. We found that the uncertainties in estimated latitudes are correlated with uncertainties in estimated longitude, tilt, and speed, showing that some CMEs are inherently difficult to fit than others. We then introduced these uncertainty values in our 3-D magnetohydrodynamic flux rope based modified spheromak CME model to figure out their consequences for space weather prediction. We find that much better CME observations are required to reliably predict magnetic field of CMEs at 1 AU using flux rope based models, since the uncertainties in estimated GCS values can result in large differences in 1 AU signatures, especially for CMEs launched away from the Sun-Earth line.
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Ensemble Simulations of the 2012 July 12 Coronal Mass Ejection with the Constant-turn Flux Rope Model
Abstract Flux-rope-based magnetohydrodynamic modeling of coronal mass ejections (CMEs) is a promising tool for prediction of the CME arrival time and magnetic field at Earth. In this work, we introduce a constant-turn flux rope model and use it to simulate the 2012 July 12 16:48 CME in the inner heliosphere. We constrain the initial parameters of this CME using the graduated cylindrical shell (GCS) model and the reconnected flux in post-eruption arcades. We correctly reproduce all the magnetic field components of the CME at Earth, with an arrival time error of approximately 1 hr. We further estimate the average subjective uncertainties in the GCS fittings by comparing the GCS parameters of 56 CMEs reported in multiple studies and catalogs. We determined that the GCS estimates of the CME latitude, longitude, tilt, and speed have average uncertainties of 5.°74, 11.°23, 24.°71, and 11.4%, respectively. Using these, we have created 77 ensemble members for the 2012 July 12 CME. We found that 55% of our ensemble members correctly reproduce the sign of the magnetic field components at Earth. We also determined that the uncertainties in GCS fitting can widen the CME arrival time prediction window to about 12 hr for the 2012 July 12 CME. On investigating the forecast accuracy introduced by the uncertainties in individual GCS parameters, we conclude that the half-angle and aspect ratio have little impact on the predicted magnetic field of the 2012 July 12 CME, whereas the uncertainties in longitude and tilt can introduce relatively large spread in the magnetic field predicted at Earth.
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- NSF-PAR ID:
- 10342182
- Date Published:
- Journal Name:
- The Astrophysical Journal
- Volume:
- 933
- Issue:
- 2
- ISSN:
- 0004-637X
- Page Range / eLocation ID:
- 123
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract The magnetic fields of interplanetary coronal mass ejections (ICMEs), which originate close to the Sun in the form of a flux rope, determine their geoeffectiveness. Therefore, robust flux rope‐based models of CMEs are required to perform magnetohydrodynamic (MHD) simulations aimed at space weather predictions. We propose a modified spheromak model and demonstrate its applicability to CME simulations. In this model, such properties of a simulated CME as the poloidal and toroidal magnetic fluxes, and the helicity sign can be controlled with a set of input parameters. We propose a robust technique for introducing CMEs with an appropriate speed into a background, MHD solution describing the solar wind in the inner heliosphere. Through a parametric study, we find that the speed of a CME is much more dependent on its poloidal flux than on the toroidal flux. We also show that the CME speed increases with its total energy, giving us control over its initial speed. We further demonstrate the applicability of this model to simulations of CME‐CME collisions. Finally, we use this model to simulate the 12 July 2012 CME and compare the plasma properties at 1 AU with observations. The predicted CME properties agree reasonably with observational data.
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Abstract The arrival time prediction of coronal mass ejections (CMEs) is an area of active research. Many methods with varying levels of complexity have been developed to predict CME arrival. However, the mean absolute error (MAE) of predictions remains above 12 hr, even with the increasing complexity of methods. In this work we develop a new method for CME arrival time prediction that uses magnetohydrodynamic simulations involving data-constrained flux-rope-based CMEs, which are introduced in a data-driven solar wind background. We found that for six CMEs studied in this work the MAE in arrival time was ∼8 hr. We further improved our arrival time predictions by using ensemble modeling and comparing the ensemble solutions with STEREO-A and STEREO-B heliospheric imager data. This was done by using our simulations to create synthetic J-maps. A machine-learning (ML) method called the lasso regression was used for this comparison. Using this approach, we could reduce the MAE to ∼4 hr. Another ML method based on the neural networks (NNs) made it possible to reduce the MAE to ∼5 hr for the cases when HI data from both STEREO-A and STEREO-B were available. NNs are capable of providing similar MAE when only the STEREO-A data are used. Our methods also resulted in very encouraging values of standard deviation (precision) of arrival time. The methods discussed in this paper demonstrate significant improvements in the CME arrival time predictions. Our work highlights the importance of using ML techniques in combination with data-constrained magnetohydrodynamic modeling to improve space weather predictions.
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Abstract Stealth coronal mass ejections (CMEs) are eruptions from the Sun that are not associated with appreciable low-coronal signatures. Because they often cannot be linked to a well-defined source region on the Sun, analysis of their initial magnetic configuration and eruption dynamics is particularly problematic. In this article, we address this issue by undertaking the first attempt at predicting the magnetic fields of a stealth CME that erupted in 2020 June from the Earth-facing Sun. We estimate its source region with the aid of off-limb observations from a secondary viewpoint and photospheric magnetic field extrapolations. We then employ the Open Solar Physics Rapid Ensemble Information modeling suite to evaluate its early evolution and forward model its magnetic fields up to Parker Solar Probe, which detected the CME in situ at a heliocentric distance of 0.5 au. We compare our hindcast prediction with in situ measurements and a set of flux-rope reconstructions, obtaining encouraging agreement on arrival time, spacecraft-crossing location, and magnetic field profiles. This work represents a first step toward reliable understanding and forecasting of the magnetic configuration of stealth CMEs and slow streamer-blowout events.
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Context. Coronal mass ejections (CMEs) are eruptions of plasma from the Sun that travel through interplanetary space and may encounter Earth. CMEs often enclose a magnetic flux rope (MFR), the orientation of which largely determines the CMEs’ geoeffectiveness. Current operational CME models do not model MFRs, but a number of research ones do, including the Open Solar Physics Rapid Ensemble Information (OSPREI) model.Aims. We report the sensitivity of OSPREI to a range of user-selected photospheric and coronal conditions.Methods. We modeled four separate CMEs observed in situ by Parker Solar Probe (PSP). We varied the input photospheric conditions using four input magnetograms (HMI Synchronic, HMI Synoptic, GONG Synoptic Zero-Point Corrected, and GONG ADAPT). To vary the coronal field reconstruction, we employed the Potential Field Source Surface (PFSS) model and varied its source-surface height in the range 1.5–3.0R ⊙with 0.1R ⊙increments.Results. We find that both the input magnetogram and PFSS source surface often affect the evolution of the CME as it propagates through the Sun’s corona into interplanetary space, and therefore the accuracy of the MFR prediction compared to in situ data at PSP. There is no obvious best combination of input magnetogram and PFSS source surface height.Conclusions. The OSPREI model is moderately sensitive to the input photospheric and coronal conditions. Based on where the source region of the CME is located on the Sun, there may be best practices when selecting an input magnetogram to use.
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3847/1538-4357/ac73f3
