Magnetic storms

1998 ◽  
pp. 57-66 ◽  
Author(s):  
Bruce T. Tsurutani ◽  
Walter D. Gonzalez
Keyword(s):  
Magnetic Storms

Models of the geomagnetic field and characteristics of magnetic storms

2006 ◽  
Vol 12 (1) ◽  
pp. 64-69
Author(s):  
O.I. Maksimenko ◽  
◽  
L.N. Yaremenko ◽  
O.Ya. Shenderovskaya ◽  
G.V. Melnyk ◽  
...  
Keyword(s):  
Geomagnetic Field ◽  
Magnetic Storms

Survey of Ring Current Composition During Magnetic Storms

1998 ◽  
Author(s):  
M. Grande ◽  
C. H. Perry ◽  
A. Hall ◽  
J. Fennell ◽  
B. Wilken
Keyword(s):  
Ring Current ◽  
Magnetic Storms

The Energetic Electron Response to Magnetic Storms: HEO Satellite Observations

2004 ◽  
Author(s):  
J. F. Fennell ◽  
J. B. Blake ◽  
R. Friedel ◽  
S. Kanekal
Keyword(s):  
Energetic Electron ◽  
Magnetic Storms ◽  
Satellite Observations

scholarly journals Observation evidences of atmospheric Gravity Waves induced by seismic activity from analysis of subionospheric LF signal spectra

2007 ◽  
Vol 7 (5) ◽  
pp. 625-628 ◽  
Author(s):  
A. Rozhnoi ◽  
M. Solovieva ◽  
O. Molchanov ◽  
P.-F. Biagi ◽  
M. Hayakawa
Keyword(s):  
Gravity Waves ◽  
Fresnel Zone ◽  
Signal Amplitude ◽  
Magnetic Storms ◽  
Frequency Range ◽  
Atmospheric Gravity Waves ◽  
Period Range ◽  
Before And After ◽  
Atmospheric Gravity ◽  
Large Earthquakes

Abstract. We analyze variations of the LF subionospheric signal amplitude and phase from JJY transmitter in Japan (F=40 kHz) received in Petropavlovsk-Kamchatsky station during seismically quiet and active periods including also periods of magnetic storms. After 20 s averaging, the frequency range of the analysis is 0.28–15 mHz that corresponds to the period range from 1 to 60 min. Changes in spectra of the LF signal perturbations are found several days before and after three large earthquakes, which happened in November 2004 (M=7.1), August 2005 (M=7.2) and November 2006 (M=8.2) inside the Fresnel zone of the Japan-Kamchatka wavepath. Comparing the perturbed and background spectra we have found the evident increase in spectral range 10–25 min that is in the compliance with theoretical estimations on lithosphere-ionosphere coupling by the Atmospheric Gravity Waves (T>6 min). Similar changes are not found for the periods of magnetic storms.

scholarly journals What Solar–Terrestrial Link Researchers Should Know about Interplanetary Drivers

Universe ◽  
2021 ◽  
Vol 7 (5) ◽  
pp. 138
Author(s):  
Yuri I. Yermolaev ◽  
Irina G. Lodkina ◽  
Lidia A. Dremukhina ◽  
Michael Y. Yermolaev ◽  
Alexander A. Khokhlachev
Keyword(s):  
Interplanetary Shock ◽  
Magnetic Storms ◽  
System Response ◽  
Ionospheric Disturbances ◽  
Atmosphere System ◽  
Compression Region ◽  
Different Types ◽  
Methodological Approaches ◽  
Composite Nature ◽  
Incorrect Data

One of the most promising methods of research in solar–terrestrial physics is the comparison of the responses of the magnetosphere–ionosphere–atmosphere system to various types of interplanetary disturbances (so-called “interplanetary drivers”). Numerous studies have shown that different types of drivers result in different reactions of the system for identical variations in the interplanetary magnetic field. In particular, the sheaths—compression regions before fast interplanetary CMEs (ICMEs)—have higher efficiency in terms of the generation of magnetic storms than ICMEs. The growing popularity of this method of research is accompanied by the growth of incorrect methodological approaches in such studies. These errors can be divided into four main classes: (i) using incorrect data with the identification of driver types published in other studies; (ii) using incorrect methods to identify the types of drivers and, as a result, misclassify the causes of magnetospheric-ionospheric disturbances; (iii) ignoring a frequent case with a complex, composite, nature of the driver (the presence of a sequence of several simple drivers) and matching the system response with only one of the drivers; for example, a magnetic storm is often generated by a sheath in front of ICME, although the authors consider these events to be a so-called “CME-induced” storm, rather than a “sheath-induced” storm; (iv) ignoring the compression regions before the fast CME in the case when there is no interplanetary shock (IS) in front of the compression region (“sheath without IS” or the so-called “lost driver”), although this type of driver generates about 10% of moderate and large magnetic storms. Possible ways of solving this problem are discussed.

Longitudinal variations of geomagnetic and ionospheric parameters in the Northern Hemisphere during magnetic storms according to multi-instrument observations

2021 ◽  
Vol 67 (2) ◽  
pp. 762-776
Author(s):  
M.A. Chernigovskaya ◽  
B.G. Shpynev ◽  
A.S. Yasyukevich ◽  
D.S. Khabituev ◽  
K.G. Ratovsky ◽  
...  
Keyword(s):  
Northern Hemisphere ◽  
Magnetic Storms ◽  
Longitudinal Variations

scholarly journals Extreme geomagnetic activities: a statistical study

2020 ◽  
Vol 72 (1) ◽  
Author(s):  
Ryuho Kataoka
Keyword(s):  
Magnetic Storms ◽  
Magnetic Observatory ◽  
Statistical Distributions ◽  
Limited Data ◽  
Data Set ◽  
Sudden Commencements ◽  
The One ◽  
Log Normal ◽  
Geomagnetic Activities ◽  
Log Normal Distribution

Abstract Statistical distributions are investigated for magnetic storms, sudden commencements (SCs), and substorms to identify the possible amplitude of the one in 100-year and 1000-year events from a limited data set of less than 100 years. The lists of magnetic storms and SCs are provided from Kakioka Magnetic Observatory, while the lists of substorms are obtained from SuperMAG. It is found that majorities of events essentially follow the log-normal distribution, as expected from the random output from a complex system. However, it is uncertain that large-amplitude events follow the same log-normal distributions, and rather follow the power-law distributions. Based on the statistical distributions, the probable amplitudes of the 100-year (1000-year) events can be estimated for magnetic storms, SCs, and substorms as approximately 750 nT (1100 nT), 230 nT (450 nT), and 5000 nT (6200 nT), respectively. The possible origin to cause the statistical distributions is also discussed, consulting the other space weather phenomena such as solar flares, coronal mass ejections, and solar energetic particles.

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