Using ghost fronts within STEREO Heliospheric Imager data to infer the evolution in longitudinal structure of a coronal mass ejectionScott, C. J. ORCID: https://orcid.org/0000-0001-6411-5649, Owens, M. J., de Koning, C. A., Barnard, L. A., Jones, S. R. and Wilkinson, J. (2019) Using ghost fronts within STEREO Heliospheric Imager data to infer the evolution in longitudinal structure of a coronal mass ejection. Space Weather, 17 (4). pp. 539-552. ISSN 1542-7390
It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.1029/2018SW002093 Abstract/SummaryImages of coronal mass ejections (CMEs) from the Heliospheric Imager (HI) instruments on board the STEREO spacecraft frequently contain rich structure. Here, we present analysis of the Earth-directed CME launched on 12 December 2008 in which we intepret the revealed structure as projections of separate discrete sections of the physical boundary of the CME. By comparing the relative position of the outer and inner 'ghost' fronts seen in the STEREO HI1 cameras with the positions of features determined from three CME models we show that the two fronts seen in the images correspond to the expected position of the flank and nose of the CME where the background solar wind is uniform. In contrast, the flank of the CME observed expanding into a structured background solar wind results in the elongation between the two fronts being greater than expected. This is consistent with the CME flank distorting in the presence of a high-speed solar wind stream. Further work is required to consolidate these results. The presence of a shock for this event was ruled out by consideration of the low CME speed and by studying in-situ spacecraft data. The CME flank crossing the Thomson sphere was also ruled out as a cause of the ghost fronts. Ghost fronts could provide information about the longitudinal shape of the CME independent of geometric models. This technique could subsequently be used to improve space weather forecast models through techniques such as data assimilation.
Download Statistics DownloadsDownloads per month over past year Altmetric Funded Project Deposit Details University Staff: Request a correction | Centaur Editors: Update this record |