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

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 similar to 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 similar to 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. Space weather refers to the changing conditions in space, largely influenced by massive eruptions from the Sun. We call these eruptions "Coronal mass ejections" or "CMEs." Earth-directed CMEs produce geomagnetic storms that affect our satellites, communication systems, and power grids, causing disruptions in our technology and infrastructure. Hence, how fast CMEs move and how wide they are in 3D space is crucial to predicting their arrival on Earth. To trace these eruptions in 3D, we use a geometrical model on a large set of CMEs during low and high solar activity from different angles, like figuring out the path of a flying bird from different angles. Derived 3D characteristics such as speed and width (size) compared to the values obtained from one angle (like watching the bird from only one spot) gives us a better idea of how fast they are going. Some eruptions were slow, while others were faster. The bigger the eruption, the faster it tends to be. Our results highlight that the 3D aspect of CMEs is crucial for issuing timely warnings and taking necessary precautions to safeguard our technology and prevent potential damages caused by space weather events. Presents a large multi-viewpoint data set containing 3D (true) speeds, 3D (true) widths, locations, and source regions of 360 Coronal Mass Ejections (CMEs) observed during the solar cycle 24 Statistical analysis of true speed and width of CMEs with and without source region separation is compared to the projected values Corrected speed and width to be used as initial conditions in space weather forecasting models for better arrival time predictions at Earth