Modeling of solar wind control of the ring current buildup: A case study of the magnetic storms in April 1997

1998 ◽  
Vol 25 (20) ◽  
pp. 3751-3754 ◽  
Author(s):  
Y. Ebihara ◽  
M. Ejiri
Keyword(s):  
Solar Wind ◽  
Ring Current ◽  
Magnetic Storms

scholarly journals Transfer entropy and cumulant based cost as measures of nonlinear causal relationships in space plasmas: applications to <i>D<sub><i>st</i></i>

2018 ◽  
Author(s):  
Jay R. Johnson ◽  
Simon Wing ◽  
Enrico Camporeale
Keyword(s):  
Solar Wind ◽  
Mutual Information ◽  
Strong Correlation ◽  
Information Transfer ◽  
Ring Current ◽  
Space Physics ◽  
Transfer Entropy ◽  
Linear Relationships ◽  
Transfer Of Information

Abstract. It is well known that the magnetospheric response to the solar wind is nonlinear. Information theoretical tools such as mutual information, transfer entropy, and cumulant based analysis are able to characterize the nonlinearities in the system. Using cumulant based cost, we show that nonlinear significance of Dst peaks at 3–12 hours lags that can be attributed to VBs which also exhibit similar behavior. However, the nonlinear significance that peaks at lags 25, 50, and 90 hours can be attributed to internal dynamics, which may be related to the relaxation of the ring current. These peaks are absent in the linear and nonlinear self-significance of VBs. Our analysis with mutual information and transfer entropy show that both methods can establish that there are a strong correlation and transfer of information from Vsw to Dst at a time scale that is consistent with that obtained from the cumulant based analysis. However, mutual information also shows that there is a strong correlation in the backward direction, from Dst to Vsw, which is counterintuitive. In contrast, transfer entropy shows that there is no or little transfer of information from Dst to Vsw, as expected because it is the solar wind that drives the magnetosphere, not the other way around. Our case study demonstrates that these information theoretical tools are quite useful for space physics studies because these tools can uncover nonlinear dynamics that cannot be seen with the traditional analyses and models that assume linear relationships.

Identification of the ground signatures of magnetospheric current systems as a function of latitude during intense magnetic storms

2021 ◽  
Author(s):  
Vasilis Pitsis ◽  
Georgios Balasis ◽  
Ioannis Daglis ◽  
Dimitris Vassiliadis
Keyword(s):  
Solar Wind ◽  
Magnetic Fields ◽  
Geomagnetic Field ◽  
Ring Current ◽  
Magnetic Storms ◽  
Quiet Time ◽  
Maximum Correlation ◽  
Current Form ◽  
H Index ◽  
Current Systems

&lt;p&gt;We show that changes in the magnetospheric ring current and auroral currents during the magnetic storms of March 2015 and June 2015, are recorded in several specific ways by ground magnetometers. The ring current changes are detected in geomagnetic field measurements of ground stations at magnetic mid-latitudes from -50 to +50 degrees. The auroral currents changes are detected at high magnetic latitudes from 50 to about 73 degrees. Finally, for stations between 73 and about 85 degrees the measurements of the ground magnetometers seem to be directly correlated with the convection electric field VB&lt;sub&gt;South&lt;/sub&gt; of the solar wind. Using the correlations among magnetic fields measured at stations ordered by latitude, a correlation diagram is obtained where the maximum correlation values for fields determined by the ring current form a distinct block. High-latitude magnetic fields from stations at higher latitudes, which are mainly determined by auroral currents, form a different block in the same diagram. This is in agreement with our earlier work using wavelet transforms on ground magnetic-field time series, where mid-latitude fields stations that are influenced mainly by the ring current, give a critical exponent greater than 2 while higher-latitude fields show a more complex dependence with two exponents. The maximum correlation values for mid-latitude fields correlated with the SYM-H index vary from 0.8 to 0.9, and, thus, we infer that those geomagnetic disturbances are mainly due to the ring current. The maximum correlations between the same fields and the solar wind VB&lt;sub&gt;South &lt;/sub&gt;vary from 0.5 to 0.7. Fields at magnetic latitudes between 50 and 73 degrees exhibit greater correlation values for the AL index rather than the SYM-H index. This is expected since in the auroral zone, the convection- and substorm-associated auroral electrojets contribute significantly to the deviation of the geomagnetic field from its quiet-time value. In this case, maximum correlations vary between 0.6 and 0.7 for auroral latitude stations when compared with AL, as opposed to 0.4&amp;#8211;0.5 when compared with SYM-H. Our results show how different measures of ground geomagnetic variations reflect the time evolution of several magnetospheric current systems and of the solar wind &amp;#8211; magnetosphere coupling.&lt;/p&gt;

scholarly journals Transfer entropy and cumulant-based cost as measures of nonlinear causal relationships in space plasmas: applications to <i>D</i><sub>st</sub>

2018 ◽  
Vol 36 (4) ◽  
pp. 945-952 ◽  
Author(s):  
Jay R. Johnson ◽  
Simon Wing ◽  
Enrico Camporeale
Keyword(s):  
Solar Wind ◽  
Mutual Information ◽  
Information Transfer ◽  
Ring Current ◽  
Space Physics ◽  
Transfer Entropy ◽  
Strong Correlations ◽  
Linear Relationships ◽  
Transfer Of Information

Abstract. It is well known that the magnetospheric response to the solar wind is nonlinear. Information theoretical tools such as mutual information, transfer entropy, and cumulant-based analysis are able to characterize the nonlinearities in the system. Using cumulant-based cost, we show that nonlinear significance of Dst peaks at 3–12 h lags that can be attributed to VBs, which also exhibits similar behavior. However, the nonlinear significance that peaks at lags 25, 50, and 90 h can be attributed to internal dynamics, which may be related to the relaxation of the ring current. These peaks are absent in the linear and nonlinear self-significance of VBs. Our analysis with mutual information and transfer entropy shows that both methods can establish that there are strong correlations and transfer of information from Vsw to Dst at a timescale that is consistent with that obtained from the cumulant-based analysis. However, mutual information also shows that there is a strong correlation in the backward direction, from Dst to Vsw, which is counterintuitive. In contrast, transfer entropy shows that there is no or little transfer of information from Dst to Vsw, as expected because it is the solar wind that drives the magnetosphere, not the other way around. Our case study demonstrates that these information theoretical tools are quite useful for space physics studies because these tools can uncover nonlinear dynamics that cannot be seen with the traditional analyses and models that assume linear relationships.

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

scholarly journals Prediction of SYM-H index during large storms by NARX neural network from IMF and solar wind data

2010 ◽  
Vol 28 (2) ◽  
pp. 381-393 ◽  
Author(s):  
L. Cai ◽  
S. Y. Ma ◽  
Y. L. Zhou
Keyword(s):  
Neural Network ◽  
Solar Wind ◽  
Correlation Coefficient ◽  
Characteristic Time ◽  
Ring Current ◽  
Wind Data ◽  
Distinct Advantage ◽  
Elman Network ◽  
H Index ◽  
Narx Neural Network

Abstract. Similar to the Dst index, the SYM-H index may also serve as an indicator of magnetic storm intensity, but having distinct advantage of higher time-resolution. In this study the NARX neural network has been used for the first time to predict SYM-H index from solar wind (SW) and IMF parameters. In total 73 time intervals of great storm events with IMF/SW data available from ACE satellite during 1998 to 2006 are used to establish the ANN model. Out of them, 67 are used to train the network and the other 6 samples for test. Additionally, the NARX prediction model is also validated using IMF/SW data from WIND satellite for 7 great storms during 1995–1997 and 2005, as well as for the July 2000 Bastille day storm and November 2001 superstorm using Geotail and OMNI data at 1 AU, respectively. Five interplanetary parameters of IMF Bz, By and total B components along with proton density and velocity of solar wind are used as the original external inputs of the neural network to predict the SYM-H index about one hour ahead. For the 6 test storms registered by ACE including two super-storms of min. SYM-H<−200 nT, the correlation coefficient between observed and NARX network predicted SYM-H is 0.95 as a whole, even as high as 0.95 and 0.98 with average relative variance of 13.2% and 7.4%, respectively, for the two super-storms. The prediction for the 7 storms with WIND data is also satisfactory, showing averaged correlation coefficient about 0.91 and RMSE of 14.2 nT. The newly developed NARX model shows much better capability than Elman network for SYM-H prediction, which can partly be attributed to a key feedback to the input layer from the output neuron with a suitable length (about 120 min). This feedback means that nearly real information of the ring current status is effectively directed to take part in the prediction of SYM-H index by ANN. The proper history length of the output-feedback may mainly reflect on average the characteristic time of ring current decay which involves various decay mechanisms with ion lifetimes from tens of minutes to tens of hours. The Elman network makes feedback from hidden layer to input only one step, which is of 5 min for SYM-H index in this work and thus insufficient to catch the characteristic time length.

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