Correcting Projection Effects in CMEs Using GCS-Based Large Statistics of Multi-Viewpoint Observations

Harshita Gandhi* (Lead Author), Ritesh Patel, Vaibhav Pant, Satabdwa Majumdar, Sanchita Pal, Dipankar Banerjee, Huw Morgan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

17 Downloads (Pure)

Abstract

This study addresses the limitations of single-viewpoint observations of Coronal Mass Ejections (CMEs) by presenting results from a 3D catalog of 360 CMEs during solar cycle 24, fitted using the Graduated Cylindrical Shell (GCS) model. The data set combines 326 previously analyzed CMEs and 34 newly examined events, categorized by their source regions into active region (AR) eruptions, active prominence (AP) eruptions, and prominence eruptions (PE). Estimates of errors are made using a bootstrapping approach. The findings highlight that the average 3D speed of CMEs is ∼1.3 times greater than the 2D speed. PE CMEs tend to be slow, with an average speed of 432 km s−1. AR and AP speeds are higher, at 723 and 813 km s−1, respectively, with the latter having fewer slow CMEs. The distinctive behavior of AP CMEs is attributed to factors like overlying magnetic field distribution or geometric complexities leading to less accurate GCS fits. A linear fit of projected speed to width gives a gradient of ∼2 km s−1 deg−1, which increases to 5 km s−1 deg−1 when the GCS-fitted ‘true’ parameters are used. Notably, AR CMEs exhibit a high gradient of 7 km s−1 deg−1, while AP CMEs show a gradient of 4 km s−1 deg−1. PE CMEs, however, lack a significant speed-width relationship. We show that fitting multi-viewpoint CME images to a geometrical model such as GCS is important to study the statistical properties of CMEs, and can lead to a deeper insight into CME behavior that is essential for improving future space weather forecasting.
Original languageEnglish
Article numbere2023SW003805
Number of pages20
JournalSpace Weather
Volume22
Issue number2
DOIs
Publication statusPublished - 19 Feb 2024

Keywords

  • Coronal mass ejections, kinematics, space weather
  • multi‐viewpoint
  • forward modeling
  • kinematics
  • stereoscopy
  • bootstrap
  • middle corona
  • coronal mass ejection
  • corona
  • Atmospheric Science
  • multi-viewpoint

Fingerprint

Dive into the research topics of 'Correcting Projection Effects in CMEs Using GCS-Based Large Statistics of Multi-Viewpoint Observations'. Together they form a unique fingerprint.

Cite this