The role of aerodynamic drag in dynamics of coronal mass ejections

Vršnak, Bojan; Vrbanec, Dijana; Čalogović, Jaša; Žic, Tomislav

doi:10.1017/s1743921309029391

Cited by 8 publications

(7 citation statements)

References 18 publications

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“…The importance of drag becomes further apparent through the CME interaction with a slow-speed solar wind stream ahead of it, slowing it to a speed that accounts for the observed arrival time at L1 near Earth. This agrees with the conjecture that Sun-Earth transit time is more closely related to the solar wind speed than the initial CME speed 52 . Other kinematic studies of this CME through the HI fields-of-view quote velocities of 411 ± 23 km s −1 (Ahead) and 417 ± 15 km s −1 (Behind) when assumed to have zero acceleration during this late phase of propagation 34 , or an average of 363 ± 43 km s −1 when triangulated in time-elongation J-maps 36 .…”

Section: Discussionsupporting

confidence: 91%

Propagation of an Earth-directed coronal mass ejection in three dimensions

et al. 2010

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Solar coronal mass ejections (CMEs) are the most signifi cant drivers of adverse space weather on Earth, but the physics governing their propagation through the heliosphere is not well understood. Although stereoscopic imaging of CMEs with NASA's Solar Terrestrial Relations Observatory (STEREO) has provided some insight into their three-dimensional (3D) propagation, the mechanisms governing their evolution remain unclear because of diffi culties in reconstructing their true 3D structure. In this paper, we use a new elliptical tie-pointing technique to reconstruct a full CME front in 3D, enabling us to quantify its defl ected trajectory from high latitudes along the ecliptic, and measure its increasing angular width and propagation from 2 to 46 R ( ~ 0.2 AU). Beyond 7 R , we show that its motion is determined by an aerodynamic drag in the solar wind and, using our reconstruction as input for a 3D magnetohydrodynamic simulation, we determine an accurate arrival time at the Lagrangian L1 point near Earth.

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Section: Discussionsupporting

confidence: 91%

Propagation of an Earth-directed coronal mass ejection in three dimensions

et al. 2010

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“…The drag-based model is often used assuming that the Lorentz and gravity forces decrease such that the drag force can largely govern CME dynamics far from the Sun. Although it is not proven that drag is the only force that shapes CME dynamics in the interplanetary medium, the observed deceleration/acceleration of some CMEs has been closely reproduced by considering only the drag force acting between the CME and the ambient solar wind medium (Lindsay et al 1999;Cargill 2004;Manoharan 2006;Vršnak et al 2009;Lara & Borgazzi 2009). In the STEREO era, with the formulation of several 3D reconstruction methods, the 3D kinematics of CMEs estimated in COR2 and HI FOV is used to estimate their arrival time at Earth (Mishra & Srivastava 2013;Mishra et al 2015).…”

Section: Drag Based Model For Propagation Of Cmesmentioning

confidence: 99%

Propagation of Coronal Mass Ejections from the Sun to Earth

Mishra¹,

Teriaca²

2022

Preprint

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Coronal Mass Ejections (CMEs), as they can inject a large amounts of mass and magnetic flux into the interplanetary space, are the primary source of space weather phenomena on the Earth. The present review first briefly introduces the solar surface signatures of the origins of CMEs and then focuses on the attempts to understand the kinematic evolution of CMEs from the Sun to the Earth. CMEs have been observed in the solar corona in whitelight from a series of space missions over the last five decades. In particular, LASCO/SOHO has provided almost continuous coverage of CMEs for more than two solar cycles until today. However, the observations from LASCO suffered from projection effects and limited field of view (within 30 R from the Sun). The launch in 2006 of the twin STEREO spacecraft made possible multiple viewpoints imaging observations, which enabled us to assess the projection effects on CMEs. Moreover, heliospheric imagers (HIs) onboard STEREO continuously observed the large and unexplored distance gap between the Sun and Earth. Finally, the Earth-directed CMEs that before have been routinely identified only near the Earth at 1 AU in in situ observations from ACE and WIND, could also be identified at longitudes away from the Sun-Earth line using the in situ instruments onboard STEREO. We describe the key signatures for the identification of CMEs using in situ observations. Our review presents the frequently used methods for estimation of the kinematics of CMEs and their arrival time at 1 AU using primarily SOHO and STEREO observations. We emphasize the need of deriving the three-dimensional (3D) properties of Earth-directed CMEs from the locations away from the Sun-Earth line. The results improving the CME arrival time prediction at Earth and the open issues holding back progress are also discussed. Finally, we summarize the importance of heliospheric imaging and discuss the path forward to achieve improved space weather forecasting.

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“…At heliocentric distances beyond R 15, the MHD drag becomes a dominant force (Vršnak et al 2009), so the CME motion is basically influenced solely by the F d term of the force Equation (1).…”

Section: The Drag Forcementioning

confidence: 99%

“…where c d refers to the dimensionless drag coefficient, A is the cross section of the CME, ρ represents the ambient solar wind density, and (v − w) is the velocity difference between the CME and the solar wind (Chen 1989;Chen & Garren 1993;Cargill et al 1996Cargill et al , 2000Cargill & Schmidt 2002;Vršnak & Gopalswamy 2002;Vršnak et al 2004Vršnak et al , 2009Vršnak et al , 2010.…”

Section: The Drag Forcementioning

confidence: 99%

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Heliospheric Propagation of Coronal Mass Ejections: Drag-Based Model Fitting

Žic

Vršnak

Temmer

2015

ApJS

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The so-called drag-based model (DBM) simulates analytically the propagation of coronal mass ejections (CMEs) in interplanetary space and allows the prediction of their arrival times and impact speeds at any point in the heliosphere ("target"). The DBM is based on the assumption that beyond a distance of about 20 solar radii from the Sun, the dominant force acting on CMEs is the "aerodynamic" drag force. In the standard form of DBM, the user provisionally chooses values for the model input parameters, by which the kinematics of the CME over the entire Sun-"target" distance range is defined. The choice of model input parameters is usually based on several previously undertaken statistical studies. In other words, the model is used by ad hoc implementation of statistics-based values of the input parameters, which are not necessarily appropriate for the CME under study. Furthermore, such a procedure lacks quantitative information on how well the simulation reproduces the coronagraphically observed kinematics of the CME, and thus does not provide an estimate of the reliability of the arrival prediction. In this paper we advance the DBM by adopting it in a form that employs the CME observations over a given distance range to evaluate the most suitable model input parameters for a given CME by means of the least-squares fitting. Furthermore, the new version of the model automatically responds to any significant change of the conditions in the ambient medium (solar wind speed, density, CME-CME interactions, etc.) by changing the model input parameters according to changes in the CME kinematics. The advanced DBM is shaped in a form that can be readily employed in an operational system for real-time space-weather forecasting by promptly adjusting to a successively expanding observational dataset, thus providing a successively improving prediction of the CME arrival.-3 -

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The role of aerodynamic drag in dynamics of coronal mass ejections

Cited by 8 publications

References 18 publications

Propagation of an Earth-directed coronal mass ejection in three dimensions

Propagation of an Earth-directed coronal mass ejection in three dimensions

Propagation of Coronal Mass Ejections from the Sun to Earth

Heliospheric Propagation of Coronal Mass Ejections: Drag-Based Model Fitting

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