Abstract Details


Name: Pritam Das
Affiliation: Aryabhatta Research Institute of Observational Sciences
Conference ID: TVS202510143
Title: Advancing CME Kinematics with Optical Flow: Multi-Coronagraph Insights into Internal Velocity Dispersion
Authors and Co-Authors: Dr. Vaibhav Pant
Abstract Type: Contributory Presentation
Abstract: Coronal Mass Ejections (CMEs) are large-scale eruptions of magnetized plasma that drive severe space weather disturbances. Understanding their kinematics in the poorly explored middle corona is critical for bridging CME initiation with their interplanetary evolution. Traditional approaches, which rely on manually tracking CME features at selected position angles, are subjective and restricted, often masking the internal velocity dispersion that arises between different CME structures such as the core and leading edge or their sub-structures. In this work, we employ state-of-the-art optical flow (OF) techniques to extract the full two-dimensional velocity field of CMEs from coronagraph observations. Optical flow tracks outward motions by capturing spatiotemporal intensity variations, allowing us to probe CME dynamics across their entire structure rather than at isolated angles. We implement OF on datasets from SOHO/LASCO C2, STEREO/COR1, and Solar Orbiter/METIS, thereby covering a broad range of coronal heights and viewing geometries. Extensive pre- and post-processing steps are applied to suppress instrumental noise and enhance CME to background contrast, which are essential for robust velocity estimation in faint middle-corona regimes. We present case studies where optical flow–derived velocities are systematically compared with traditional feature-tracking methods. This enables us to identify conditions under which OF provides improved measurements and to quantify discrepancies where it may be less reliable. A key outcome of our analysis is the detection of internal velocity dispersion within CMEs, which provides new insights into their expansion and deformation. Our long-term goal is to develop an automated CME detection and characterization pipeline based on OF-derived velocity distributions. Such an approach will enhance our ability to monitor CME evolution continuously and objectively, offering a pathway toward improved space-weather forecasting capabilities.