The kinematics of coronal mass ejections using multiscale methods
Astrophysics Research Group, School of Physics, Trinity College Dublin, Dublin 2, Ireland e-mail: firstname.lastname@example.org
2 ADNET Systems Inc., NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA
Accepted: 16 December 2008
Aims. The diffuse morphology and transient nature of coronal mass ejections (CMEs) make them difficult to identify and track using traditional image processing techniques. We apply multiscale methods to enhance the visibility of the faint CME front. This enables an ellipse characterisation to objectively study the changing morphology and kinematics of a sample of events imaged by the Large Angle Spectrometric Coronagraph (LASCO) onboard the Solar and Heliospheric Observatory (SOHO) and the Sun Earth Connection Coronal and Heliospheric Investigation (SECCHI) onboard the Solar Terrestrial Relations Observatory (STEREO). The accuracy of these methods allows us to test the CMEs for non-constant acceleration and expansion.
Methods. We exploit the multiscale nature of CMEs to extract structure with a multiscale decomposition, akin to a Canny edge detector. Spatio-temporal filtering highlights the CME front as it propagates in time. We apply an ellipse parameterisation of the front to extract the kinematics (height, velocity, acceleration) and changing morphology (width, orientation).
Results. The kinematic evolution of the CMEs discussed in this paper have been shown to differ from existing catalogues. These catalogues are based upon running-difference techniques that can lead to over-estimating CME heights. Our resulting kinematic curves are not well-fitted with the constant acceleration model. It is shown that some events have high acceleration below ~5 . Furthermore, we find that the CME angular widths measured by these catalogues are over-estimated, and indeed for some events our analysis shows non-constant CME expansion across the plane-of-sky.
Key words: Sun: coronal mass ejections (CMEs) / Sun: activity / techniques: image processing / methods: data analysis
© ESO, 2009