Dynamic evolution of the transition zone plasma in solar flares and active region transients

1986 ◽  
Vol 309 ◽  
pp. 421 ◽  
Author(s):  
Chung-Chieh Cheng ◽  
E. Tandberg-Hanssen
Keyword(s):  
Active Region ◽  
Transition Zone ◽  
Solar Flares ◽  
Dynamic Evolution

The chromosphere-corona transition zone above an active region

1984 ◽  
Vol 4 (8) ◽  
pp. 63-66 ◽  
Author(s):  
O. Kjeldseth Moe ◽  
Ø. Andreassen ◽  
P. Maltby ◽  
J.-D.F. Bartoe ◽  
G.E. Brueckner ◽  
...  
Keyword(s):  
Active Region ◽  
Transition Zone

scholarly journals The Evolution of Unstable 'Beta-Gamma' Magnetic Fields of Active Region AR 2222

2015 ◽  
Vol 48 ◽  
pp. 95-102
Author(s):  
Zety Sharizat Hamidi ◽  
S.N.U. Sabri ◽  
N.N.M. Shariff ◽  
C. Monstein
Keyword(s):  
Active Region ◽  
Magnetic Fields ◽  
Solar Corona ◽  
Solar Flares ◽  
Active Regions ◽  
Group Type ◽  
Solar Burst ◽  
Type Iv ◽  
Fine Structures ◽  
Using Data

This event allows us to investigate how plasma–magnetic field interactions in the solar corona can produce suprathermal electron populations over periods from tens of minutes to several hours, and the interactions of wave-particle and wave-wave lead to characteristic fine structures of the emission. An intense and broad solar radio burst type IV was recorded by CALLISTO spectrometer from 240-360 MHz. Using data from a the KRIM observatory, we aim to provide a comprehensive description of the synopsis formation and dynamics of a a single solar burst type IV event due to active region AR2222. For five minutes, the event exhibited strong pulsations on various time scales and “broad patterns” with a formation of a group type III solar burst. AR 2222 remained the most active region, producing a number of minor C-Class solar flares. The speed of the solar wind also exceeds 370.8 km/second with 10.2 g/cm3 density of proton in the solar corona. The radio flux also shows 171 SFU. Besides, there are 3 active regions, AR2217, AR2219 and AR2222 potentially pose a threat for M-class solar flares. Active region AR2222 have unstable 'beta-gamma' magnetic fields that harbor energy for M-class flares. As a conclusion, we believed that Sun’s activities more active in order to achieve solar maximum cycle at the end of 2014.

scholarly journals AFS dynamic evolution during the emergence of an active region

2004 ◽  
Vol 425 (1) ◽  
pp. 309-319 ◽  
Author(s):  
D. Spadaro ◽  
S. Billotta ◽  
L. Contarino ◽  
P. Romano ◽  
F. Zuccarello
Keyword(s):  
Active Region ◽  
Dynamic Evolution

Ensemble Forecasting of Major Solar Flares with Short-, Mid-, and Long-term Active Region Properties

2019 ◽  
Vol 885 (1) ◽  
pp. 35
Author(s):  
Daye Lim ◽  
Yong-Jae Moon ◽  
Eunsu Park ◽  
Jongyeob Park ◽  
Kangjin Lee ◽  
...  
Keyword(s):  
Active Region ◽  
Solar Flares ◽  
Ensemble Forecasting

The energy balance and pressure in the solar transition zone for network and active region features

1979 ◽  
Vol 233 ◽  
pp. 741 ◽  
Author(s):  
K. R. Nicolas ◽  
J.-D. F. Bartoe ◽  
G. E. Brueckner ◽  
M. E. Vanhoosier
Keyword(s):  
Energy Balance ◽  
Active Region ◽  
Transition Zone ◽  
Solar Transition

scholarly journals The influence of active region information on the prediction of solar flares: an empirical model using data mining

2005 ◽  
Vol 23 (9) ◽  
pp. 3129-3138 ◽  
Author(s):  
M. Núñez ◽  
R. Fidalgo ◽  
M. Baena ◽  
R. Morales
Keyword(s):  
Data Mining ◽  
Active Region ◽  
Solar Flares ◽  
Behavior Pattern ◽  
Pattern Learning ◽  
Data Mining Approach ◽  
Region Data ◽  
Using Data ◽  
Confidence Value ◽  
Region Information

Abstract. Predicting the occurrence of solar flares is a challenge of great importance for many space weather scientists and users. We introduce a data mining approach, called Behavior Pattern Learning (BPL), for automatically discovering correlations between solar flares and active region data, in order to predict the former. The goal of BPL is to predict the interval of time to the next solar flare and provide a confidence value for the associated prediction. The discovered correlations are described in terms of easy-to-read rules. The results indicate that active region dynamics is essential for predicting solar flares.

scholarly journals Properties of quasi-periodic pulsations in solar flares from a single active region

2017 ◽  
Vol 608 ◽  
pp. A101 ◽  
Author(s):  
C. E. Pugh ◽  
V. M. Nakariakov ◽  
A.-M. Broomhall ◽  
A. V. Bogomolov ◽  
I. N. Myagkova
Keyword(s):  
Active Region ◽  
Solar Flares

scholarly journals A Test to Confirm the Source of Energy for Solar Flares

2001 ◽  
Vol 18 (4) ◽  
pp. 351-354 ◽  
Author(s):  
M. S. Wheatland
Keyword(s):  
Active Region ◽  
Solar Flares ◽  
Large Scale ◽  
Virial Theorem ◽  
Magnetic Energy ◽  
Sufficient Data ◽  
Statistical Comparison ◽  
Independent Measure ◽  
Vector Magnetograms ◽  
Current Systems

AbstractA test of the hypothesis that flares derive their energy from large scale current systems inferred from active region vector magnetograms is proposed. The test involves a statistical comparison of the flarerelated change in coronal magnetic energy (based on the magnetohydrodynamic virial theorem) and an independent measure of the energy of the flare. A simulation suggests that — assuming the hypothesis is correct—the test requires around 50 flares with energy greater than 5×1023 J to return a significant result. Existing archives of vector magnetograms should provide sufficient data for such a study.

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