Abstract:
Coronal mass ejections (CMEs) are the most energetic and important solar activity.
They are often associated with other solar phenomena such as flares and filament/prominence
eruptions. Despite the significant improvement of CME study in the past decade, our understanding
of the initiation process of CMEs remains elusive. In order to solve this issue,
an approach that combines theoretical modelling and empirical analysis is needed. This
thesis is a combination of three studies, two of which investigate the initiation process of
CMEs, and the other is the development of a tool to automatically detect CMEs.
First, I investigate the stability of the well-known eruptive flux rope model in the context
of the torus instability. In the flux rope model, the pre-eruptive CME structure is a helical
flux rope with two footpoints anchored to the solar surface. The torus instability is dependent
on the balance between two opposing magnetic forces, the outward Lorentz self-force
(also called curvature hoop force) and the restoring Lorentz force of the ambient magnetic
fields. Previously, the condition of stability derived for the torus instability assumed that
the pre-eruptive structure was a semicircular loop above the photosphere without anchored
footpoints. I extend these results to partial torus flux ropes of any circularity with anchored
footpoints and discovered that there is a dependence of the critical index on the fractional
number of the partial torus, defined by the ratio between the arc length of the partial torus
above the photosphere and the circumference of a circular torus of equal radius. I coin this
result the partial torus instability (PTI). The result is more general than has been previously
derived and extends to loops of any arc above the photosphere. It will be demonstrated
that these results can help us understand the confinement, growth, and eventual eruption
of a flux rope CME.
Second, I use observations of eruptive prominences associated with CMEs to examine
the behaviour of their initiation and compare these observations to theoretical models. Since
theoretical models specify the pre-existence of a flux rope, the observational challenge is
the interpretation of the flux rope in solar images. A good proxy for flux ropes is prominences,
because of its obvious elongated helical structure above the magnetic polarity line.
I compare the prominence kinematics and the associated extrapolated magnetic fields. This
observational study yields two key conclusions. The first is that there is a dependence of
the ejecta’s kinematics on how the ambient magnetic field decay’s. The second is that the
critical decay index, theorized to be where the flux rope transitions from a stable to unstable
configuration, is dependent on the geometry of the loop. This second result is in qualitative
agreement with the theorized PTI.
Finally, I develop a tool to automatically detect CME events in coronagraph images.
Because of the large amount of data collected over the years, searching for candidate events
to study can be daunting. In order to facilitate the search of CME event candidates, an
algorithm was developed to automatically detect and characterize CMEs seen in coronagraph
images. With this tool, one need not scroll through the large number of images, and
only focus on particular subsets. The auto-detection reduces human bias of CME characterization.
Such automated detection algorithms can have other applications, such as space
weather alerts in near-real time.
In summary, this thesis has improved our understanding of the initiation process of
CMEs by taking both theoretical and observational studies. Future work includes investigating
a larger number of events to give a better statistical characterization of the results
found in the observational study. Furthermore, modification to the theoretical model of
the PTI, for example by including a repulsive force due to induced photospheric currents,
can improve the quantitative agreement with observations. The complete knowledge of the
initiation of CMEs is important because it can help us to predict when such an event may
occur. Such a prediction can aid in mitigating severe space weather effects at the Earth.