Kinematical properties of coronal mass ejections

Temmer, Manuela

doi:10.1002/asna.201612425

Cited by 12 publications

(6 citation statements)

References 112 publications

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“…The kinematic profiles of these events have been a major focus of research, as they hold clues about the eruption processes that drive CMEs by transforming magnetic into kinetic energy and about the potential effects of the event on space weather (Temmer 2016). Fast CMEs can drive coronal (and inner heliospheric) shocks that accelerate high-energy SEPs that pose a direct threat to space assets and human exploration (Temmer 2021).…”

Section: Introductionmentioning

confidence: 99%

The Hyper-inflation Stage in the Coronal Mass Ejection Formation: A Missing Link That Connects Flares, Coronal Mass Ejections, and Shocks in the Low Corona

Balmaceda

Vourlidas

Stenborg

et al. 2022

ApJ

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We analyze the formation and three-dimensional (3D) evolution of two coronal mass ejections (CMEs) and their associated waves in the low corona via a detailed multi-viewpoint analysis of extreme-ultraviolet observations. We analyze the kinematics in the radial and lateral directions and identify three stages in the early evolution of the CME: (1) a hyper-inflation stage, when the CME laterally expands at speeds of ∼1000 km s−1, followed by (2) a shorter and slower expansion stage of a few minutes and ending with (3) a self-similar phase that carries the CME into the middle corona. The first two stages coincide with the impulsive phase of the accompanying flare, the formation and separation of an EUV wave from the CME, and the start of the metric type II radio burst. Our 3D analysis suggests that the hyper-inflation phase may be a crucial stage in the CME formation with wide-ranging implications for solar eruption research. It likely represents the formation stage of the magnetic structure that is eventually ejected into the corona, as the white-light CME. It appears to be driven by the injection of poloidal flux into the ejecting magnetic structure, which leads to the lateral (primarily) growth of the magnetic flux rope. The rapid growth results in the creation of EUV waves and eventually shocks at the CME flanks that are detected as metric type II radio bursts. In other words, the hyper-inflation stage in the early CME evolution may be the “missing” link between CMEs, flares, and coronal shocks.

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Section: Introductionmentioning

confidence: 99%

The Hyper-inflation Stage in the Coronal Mass Ejection Formation: A Missing Link That Connects Flares, Coronal Mass Ejections, and Shocks in the Low Corona

Balmaceda

Vourlidas

Stenborg

et al. 2022

ApJ

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“…One reason for flare‐integrated flux (X‐ray fluence) being more important than flare magnitude for SEP production may be due to it being more closely associated to its corresponding CME characteristics (e.g., CME acceleration; Temmer, ). SPRINTS observation of flare decay‐phase importance for SEP production in the machine‐learning decision tree models is also consistent with Belov et al ().…”

Section: Conclusion and Remarksmentioning

confidence: 99%

SPRINTS: A Framework for Solar‐Driven Event Forecasting and Research

et al. 2017

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Capabilities to predict onset and time profiles of solar‐driven events, including solar X‐ray flares; solar energetic particles (SEP); coronal mass ejections; and high‐speed streams, are critical in mitigating their potential impacts. We introduce the Space Radiation Intelligence System (SPRINTS). This NASA‐invested technology integrates preeruptive metadata and forecasts from the MAG4 system with posteruptive metadata in order to produce high fidelity and preeruptive to posteruptive transitional forecasts for solar‐driven events. To catalog start and end times of the four solar‐driven events, SPRINTS is capable of generating posteruptive forecasts based on automatic detections employed on 30+ years of GOES X‐ray and particle data as well as 20+ years of ACE and DSCOVR solar wind data. The prediction results for 1986–2016 presented here are from the SPRINTS posteruptive capability for forecasting SEPs leveraging GOES X‐ray metadata. We present onset, peak flux, and time profile SEP forecast metrics and results based on expert‐guided, statistical, and machine‐learned decision tree models. Operating on data from a 20 year period, a machine‐learned decision tree model provided the best results for predicting an S1 event (on the NOAA Space Weather Prediction Center Solar Radiation Scale): 86% probability of detection and 37% false alarm rate. Five flare‐related metadata sets were leveraged in the decision tree modeling. Consistently, flare‐integrated flux, flare heliolongitude, and flare decay‐phase duration were found to be the top three forecasting parameters, while flare magnitude and flare latitude had little to no impact on the SEP forecast model. For the solar‐driven events of March 2012, we demonstrate SPRINTS abilities to forecast solar flares, SEP onset, and SEP evolution.

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“…This is because the local orientation of the magnetic field to the shock front strongly modulates the particle acceleration process (Guo & Giacalone, 2013). Furthermore, it has been shown that often in the early stages of eruptions the CME over-expands in the lateral direction, changing the overall shape of the compressive front ahead of it (Bein et al, 2011;Temmer, 2016). Thus, it is imperative to move beyond the idealized descriptions of the shock surfaces regularly used to model their evolution (Vourlidas et al, 2012;Kwon et al, 2014;Rouillard et al, 2016), and to employ more advanced techniques.…”

Section: Introductionmentioning

confidence: 99%

Multi-scale image preprocessing and feature tracking for remote CME characterization

Stepanyuk

Kozarev

Nedal

2022

J. Space Weather Space Clim.

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Coronal Mass Ejections (CMEs) influence the interplanetary environment over vast distances in the solar system by injecting huge clouds of fast solar plasma and energetic particles (SEPs). A number of fundamental questions remain about how SEPs are produced, but current understanding points to CME-driven shocks and compressions in the solar corona. At the same time, unprecedented remote (AIA, LOFAR, MWA) and in situ (Parker Solar Probe, Solar Orbiter) solar observations are becoming available to constrain existing theories. Here we present a general method for recognition and tracking of objects on solar images – CME shock waves, filaments, active regions. The calculation scheme is based on a multi-scale data representation concept a-trous wavelet transform, and a set of image filtering techniques. We showcase its performance on a small set of CME-related phenomena observed with the SDO/AIA telescope. With the data represented hierarchically on different decomposition and intensity levels, our method allows to extract certain objects and their masks from the imaging observations, in order to track their evolution in time. The method presented here is general and applicable to detecting and tracking various solar and heliospheric phenomena in imaging observations. We implemented this method into a freely available Python library.

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Kinematical properties of coronal mass ejections

Cited by 12 publications

References 112 publications

The Hyper-inflation Stage in the Coronal Mass Ejection Formation: A Missing Link That Connects Flares, Coronal Mass Ejections, and Shocks in the Low Corona

The Hyper-inflation Stage in the Coronal Mass Ejection Formation: A Missing Link That Connects Flares, Coronal Mass Ejections, and Shocks in the Low Corona

SPRINTS: A Framework for Solar‐Driven Event Forecasting and Research

Multi-scale image preprocessing and feature tracking for remote CME characterization

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