Analysis of Solar Eruptions Deflecting in the Low Corona

(Solar Orbiter Nugget #54 by A. Sahade¹, A. Vourlidas² and C. Mac Cormack³)

1. Introduction

Coronal mass ejections (CMEs) are the drivers of the most powerful geomagnetic storms and a major concern in space weather. A reliable prediction of an eruption and its subsequent trajectory is crucial to assess its potential threat to satellites, communication networks, or other systems. Multi-point observations, including Solar Orbiter data, have allowed the identification of CME source regions and the calculation of their 3D trajectories. We proposed a new method, based on the ambient magnetic field, to understand and predict the direction of propagation of eruptive events.
Our results suggest that the topology of the surrounding magnetic field is a dominant factor driving deflections in the low corona, making this method promising for early prediction of CME trajectories.
 

2. Computing the trajectories from 3 viewpoints

Many CMEs are related with the eruption of a filament/prominence in the low corona. This kind of eruptions is useful to follow the evolution and trajectory of the CME from its origin. Studying the trajectory evolution of eruptions requires 3D reconstruction techniques that allow us to track corresponding features observed from different points of view (POVs). The tie-pointing technique is very effective for tracking eruptions because it relies on identifying the same feature in different projections. This technique calculates the 3D coordinates of a feature by matching corresponding pixels in images taken, typically, from two different viewpoints.

Figure 1: Scheme of the orbital configuration of a prominence observed simultaneously by STEREO A, SDO and Solar Orbiter. The three-dimensional position of the prominence apex can be derived from the 2D coordinates of corresponding features in the different points of view (stars in each subpanel).

Solar Orbiter now provides a third viewpoint in the heliosphere to observe, among other things, filament eruptions. To take advantage of this, we have developed a 3D reconstruction technique that combines images from three different observatories. Figure 1 shows a schematic representation of a prominence projected by STEREO A, SDO and SOLO POV and the corresponding position of a pixel (start markers) over the different images. Dashed lines indicate the epipolar line (green for STEREO A, orange for SDO) of the selected pixel. SCC_MEASURE3 [1] uses images from 3 different viewpoints to improve the 3D reconstruction.
 

3. Deflection and magnetic ambient

Figure 2: Example of the ambient magnetic (field lines and contours of magnetic energy) and trajectory (tracked color dots and black curve showing the fitting) of an eruptive prominence on 21 March 2021 from different views, an interactive view is available here. 

It is well known that the magnetic fields surrounding the source region can alter the direction of propagation, deflecting the trajectory of CMEs, especially in their early evolution (see e.g. [2], and references therein). However, the main factor of this influence has been attributed to either the magnetic energy gradient or the topology of the magnetic field lines.
In our study [3], we explored a novel method for estimating CME deflection when the source region and background magnetic field are known. This approach calculates two magnetic paths: the 'gradient path,' which represents the trajectory of an eruption solely influenced by the magnetic energy gradient, and the 'topological path,' which corresponds to the trajectory of an eruption guided by the magnetic field lines. These paths help determine whether the eruption's deflection is mainly due to magnetic pressure or the configuration of the magnetic field lines. To assess this, we compared the magnetic paths originating from the source region with the actual eruption trajectory derived from tracking.
 

4. Conclusions

Figure 3: Example of the trajectory (color dots and black curve) compared with the topological path (orange dashed line) and gradient path (green dashed line) for the event on 31 December 2021. The white (blue) lines are closed (open) magnetic field lines near the source region.

We found that the "gradient path" is generally very different from the actual trajectory, indicating that deflections (at 2.5 Rs) can be overestimated by up to ∼20°. The "topological path", on the other hand, better describe the eruptive paths of the events studied. These results suggest rather strongly that the topology of the surrounding magnetic field may be the dominant driver for the deflection of eruptions in the low corona. Of course, the two quantities are related, since we are considering a potential magnetic field, but the topology takes into account not only the strength of the magnetic field, but also its connectivity and "shape". Clearly, the latter are important factors to consider in the evolution of CMEs.

In summary, we presented a new method for interpreting the very early path of an eruption. The topological and gradient methods rely only on the source-region location and the 3D structure of the background coronal field. CME measurements are not required. These properties make the topological method a potentially powerful addition to the present forecasting infrastructure.
 

Affiliations

(1) NASA Goddard Space Flight Center, MD, USA
(2) The Johns Hopkins University Applied Physics Laboratory, MD, USA
(3) The Catholic University of America, DC, USA
 

Acknowledgements

A.S. was supported by an appointment to the NASA Postdoctoral Program at the NASA Goddard Space Flight Center, administered by Oak Ridge Associated Universities under contract with NASA. A.V. was supported by NASA grant 80NSSC21K1860. C.M. was supported by an appointment to the Solar Orbiter Heliospheric Imager (SoloHI). The SoloHI instrument was designed, built, and is now operated by the US Naval Research Laboratory with the support of the NASA Heliophysics Division, Solar Orbiter Collaboration Office, under DPR NNG09EK11I. We acknowledge the use of SolO/EUI, SoloHI, SDO/AIA, SOHO/LASCO, and STEREO/EUVI, COR2 data. 

References

[1] Sahade A. (2024) scc_measure 3 v1 Zenodo, doi:10.5281/zenodo.13951841
[2] Cécere M., Costa A., Cremades H. and Stenborg G. (2023) FrASS 10:1260432
[3] Sahade A., Vourlidas A. and Mac Cormack C. (2025) ApJ 978(1):41