scholarly journals Transport of Magnetic Helicity and Dynamics of Solar Active Regions

2005 ◽  
Vol 13 ◽  
pp. 117-118 ◽  
Author(s):  
M. K. Georgoulis ◽  
B. J. LaBonte ◽  
D. M. Rust

AbstractWe introduce a method to calculate the magnetic helicity density in a given active-region vector magnetogram, and a lower limit of it, based on a linear force-free (Iff) approximation. Moreover, we provide a lower limit of the total magnetic helicity in the active region (AR). A time series of magnetograms can be used to calculate the rate of helicity transport. The results can be then correlated with manifestations of the dynamical activity in ARs, such as flares and filament eruptions.

2005 ◽  
Vol 13 ◽  
pp. 122-123
Author(s):  
Cristina H. Mandrini ◽  
Pascal Démoulin ◽  
Lidia van Driel-Gesztelyi ◽  
Sergio Dasso ◽  
Lucinda M. Green ◽  
...  

AbstractWe analyzed the long-term evolution of two active regions (ARs), NOAA 7978 and 8100, from their emergence through their decay using observations from several instruments on board SoHO (MDI, EIT and LASCO) and Yohkoh/SXT. We computed the evolution of the relative coronal magnetic helicity from one central meridian passage to the next, combining data from MDI and SXT with linear force-free models of the coronal magnetic field. Next, we calculated the injection of helicity by photospheric differential rotation using MDI magnetic maps and a mean differential rotation profile. To estimate the depletion of magnetic helicity we counted all the CMEs of which these ARs were the source, and we evaluated their helicity assuming a one to one correspondence with magnetic clouds (MCs) with an average helicity content; this value was computed for a sample of 18 clouds using a cylindrical linear force-free model. Out of our three helicity estimates (variation of coronal magnetic helicity, injection by differential rotation and ejection via CMEs) the one with the largest uncertainty is the amount of helicity ejected via CMEs. However, we determined, by modeling a particular MC using three different approaches in cylindrical geometry (two force-free models and a non force-free model with constant current), that its magnetic helicity content was nearly independent of the model used to fit in situ field observations (Dasso et al. 2003, in preparation). This result justifies our use of the average magnetic helicity value considering only a single MC model. Comparing the three components in the helicity balance (see Table 1), we find that photospheric differential rotation is a minor contributor to the AR magnetic helicity budget. CMEs carry away at least 10 times more helicity than the one differential rotation can provide. Therefore, the magnetic helicity flux needed in the global balance should come from localized photospheric motions that, at least partially, reflect the emergence of twisted flux tubes. Taking into account the magnetic flux in the ARs and the number of turns that a uniformly twisted flux tube should have to survive its rise through the convection zone, we have found that the total helicity carried away in CMEs is approximately equal to the end-to-end helicity of the flux tubes that formed these two ARs. Therefore, we conclude that most of the helicity ejected in CMEs is generated below the photosphere and emerges with the magnetic flux. Extended versions of this work were published in Demoulin et al. (2002, Astronomy & Astrophys. 382, 650) and in Green et al. (2002, Solar Phys. 208, 43), while in Mandrini et al. (2003, Astrophys. & Space Sci., 290, 319) and van Driel-Gesztelyi et al. (2003, Adv. Space Res., 32, 1855) the helicity computations were revised to include the underestimation of magnetic flux density found in MDI data. After this revision, we confirmed our former results.


2014 ◽  
Vol 785 (1) ◽  
pp. 13 ◽  
Author(s):  
Y. Liu ◽  
J. T. Hoeksema ◽  
M. Bobra ◽  
K. Hayashi ◽  
P. W. Schuck ◽  
...  

Solar Physics ◽  
2004 ◽  
Vol 223 (1-2) ◽  
pp. 39-55 ◽  
Author(s):  
Jongchul Chae ◽  
Yong-Jae Moon ◽  
Young-Deuk Park

2008 ◽  
Vol 41 (6) ◽  
pp. 893-896
Author(s):  
Piyali Chatterjee ◽  
Arnab Rai Choudhuri ◽  
Kristof Petrovay ◽  
Dibyendu Nandy

2006 ◽  
Vol 2 (14) ◽  
pp. 139-168
Author(s):  
Debi Prasad Choudhary ◽  
Michal Sobotka

AbstractKeeping in view of the modern powerful observing tools, among othersHinode(formerlySOLAR-B),STEREOand Frequency-Agile Solar Radiotelescope, and sophisticated modelling techniques, Joint Discussion 3 during the IAU General Assembly 2006 focused on the properties of magnetic field of solar active regions starting in deep interior of the Sun, from where they buoyantly rise to the coronal heights where the site of most explosive events are located. Intimately related with the active regions, the origin and evolution of the magnetic field of quiet Sun, the large scale chromospheric structures were also the focal point of the Joint Discussion. The theoretical modelling of the generation and dynamics of magnetic field in solar convective zone show that the interaction of the magnetic field with the Coriolis force and helical turbulent convection results in the tilts and twists in the emerging flux. In the photosphere, some of these fluxes appear in sunspots with field strengths up to about 6100 G. Spectro-polarimetric measurements reveal that the line of sight velocities and magnetic field of these locations are found to be uncombed and depend on depth in the atmosphere and exhibit gradients or discontinuities. The inclined magnetic fields beyond penumbra appear as moving magnetic features that do not rise above upper photospheric heights. As the flux rises, the solar chromosphere is the most immediate and intermediary layer where competitive magnetic forces begin to dominate their thermodynamic counterparts. The magnetic field at these heights is now measured using several diagnostic lines such as CaII854.2 nm, HI656.3 nm, and HeI1083.0 nm. The radio observations show that the coronal magnetic field of post flare loops are of the order of 30 G, which might represent the force-free magnetic state of active region in the corona. The temperatures at these coronal heights, derived from the line widths, are in the range from 2.4 to 3.7 million degree. The same line profile measurements indicate the existence of asymmetric flows in the corona. The theoretical extrapolation of photospheric field into coronal heights and their comparison with the observations show that there exists a complex topology with separatrices associated to coronal null points. The interaction of these structures often lead to flares and coronal mass ejections. The current MHD modelling of active region field shows that for coronal mass ejection both local active region magnetic field and global magnetic field due to the surrounding magnetic flux are important. Here, we present an extended summary of the papers presented in Joint Discussion 03 and open questions related to the solar magnetic field that are likely to be the prime issue with the modern observing facilities such asHinodeandSTEREOmissions.


2012 ◽  
Vol 64 (3) ◽  
pp. 54 ◽  
Author(s):  
Haiqing Xu ◽  
Yu Gao ◽  
Hongqi Zhang ◽  
Takashi Sakurai ◽  
Masaoki Hagino ◽  
...  

2020 ◽  
Vol 639 ◽  
pp. A44
Author(s):  
Soumitra Hazra ◽  
Gopal Sardar ◽  
Partha Chowdhury

Context. Large-scale solar eruptions significantly affect space weather and damage space-based human infrastructures. It is necessary to predict large-scale solar eruptions; it will enable us to protect the vulnerable infrastructures of our modern society. Aims. We investigate the difference between flaring and nonflaring active regions. We also investigate whether it is possible to forecast a solar flare. Methods. We used photospheric vector magnetogram data from the Solar Dynamic Observatory’s Helioseismic Magnetic Imager to study the time evolution of photospheric magnetic parameters on the solar surface. We built a database of flaring and nonflaring active regions observed on the solar surface from 2010 to 2017. We trained a machine-learning algorithm with the time evolution of these active region parameters. Finally, we estimated the performance obtained from the machine-learning algorithm. Results. The strength of some magnetic parameters such as the total unsigned magnetic flux, the total unsigned magnetic helicity, the total unsigned vertical current, and the total photospheric magnetic energy density in flaring active regions are much higher than those of the non-flaring regions. These magnetic parameters in a flaring active region evolve fast and are complex. We are able to obtain a good forecasting capability with a relatively high value of true skill statistic. We also find that time evolution of the total unsigned magnetic helicity and the total unsigned magnetic flux provides a very high ability of distinguishing flaring and nonflaring active regions. Conclusions. We can distinguish a flaring active region from a nonflaring region with good accuracy. We confirm that there is no single common parameter that can distinguish all flaring active regions from the nonflaring regions. However, the time evolution of the top two magnetic parameters, the total unsigned magnetic flux and the total unsigned magnetic helicity, have a very high distinguishing capability.


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