scholarly journals Predicting geomagnetic storms from solar-wind data using time-delay neural networks

1996 ◽  
Vol 14 (7) ◽  
pp. 679-686 ◽  
Author(s):  
H. Gleisner ◽  
H. Lundstedt ◽  
P. Wintoft
Keyword(s):  
Neural Networks ◽  
Solar Wind ◽  
Time Delay ◽  
Input Data ◽  
Ring Current ◽  
Geomagnetic Storms ◽  
Time History ◽  
Recovery Phase ◽  
Wind Data ◽  
Data Sequence

Abstract. We have used time-delay feed-forward neural networks to compute the geomagnetic-activity index Dst one hour ahead from a temporal sequence of solar-wind data. The input data include solar-wind density n, velocity V and the southward component Bz of the interplanetary magnetic field. Dst is not included in the input data. The networks implement an explicit functional relationship between the solar wind and the geomagnetic disturbance, including both direct and time-delayed non-linear relations. In this study we especially consider the influence of varying the temporal size of the input-data sequence. The networks are trained on data covering 6600 h, and tested on data covering 2100 h. It is found that the initial and main phases of geomagnetic storms are well predicted, almost independent of the length of the input-data sequence. However, to predict the recovery phase, we have to use up to 20 h of solar-wind input data. The recovery phase is mainly governed by the ring-current loss processes, and is very much dependent on the ring-current history, and thus also the solar-wind history. With due consideration of the time history when optimizing the networks, we can reproduce 84% of the Dst variance.

scholarly journals Ring current influence on auroral electrojet predictions

1999 ◽  
Vol 17 (10) ◽  
pp. 1268-1275 ◽  
Author(s):  
H. Gleisner ◽  
H. Lundstedt
Keyword(s):  
Solar Wind ◽  
Ring Current ◽  
Geomagnetic Storms ◽  
Wind Data ◽  
Common Source ◽  
Neural Net ◽  
Operational Forecasting ◽  
Storms And Substorms ◽  
Highly Correlated ◽  
Strong Control

Abstract. Geomagnetic storms and substorms develop under strong control of the solar wind. This is demonstrated by the fact that the geomagnetic activity indices Dst and AE can be predicted from the solar wind alone. A consequence of the strong control by a common source is that substorm and storm indices tend to be highly correlated. However, a part of this correlation is likely to be an effect of internal magnetospheric processes, such as a ring-current modulation of the solar wind-AE relation. The present work extends previous studies of nonlinear AE predictions from the solar wind. It is examined whether the AE predictions are modulated by the Dst index.This is accomplished by comparing neural network predictions from Dst and the solar wind, with predictions from the solar wind alone. Two conclusions are reached: (1) with an optimal set of solar-wind data available, the AE predictions are not markedly improved by the Dst input, but (2) the AE predictions are improved by Dst if less than, or other than, the optimum solar-wind data are available to the net. It appears that the solar wind-AE relation described by an optimized neural net is not significantly modified by the magnetosphere's Dst state. When the solar wind alone is used to predict AE, the correlation between predicted and observed AE is 0.86, while the prediction residual is nearly uncorrelated to Dst. Further, the finding that Dst can partly compensate for missing information on the solar wind, is of potential importance in operational forecasting where gaps in the stream of real time solar-wind data are a common occurrence.Key words. Magnetospheric physics (solar wind · magnetosphere interactions; storms and substorms)

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.

scholarly journals Role of the magnetospheric and ionospheric currents in the generation of the equatorial scintillations during geomagnetic storms

2004 ◽  
Vol 22 (9) ◽  
pp. 3195-3202 ◽  
Author(s):  
L. Z. Biktash
Keyword(s):  
Solar Wind ◽  
Electric Fields ◽  
Ring Current ◽  
Geomagnetic Storms ◽  
Equatorial Ionosphere ◽  
Experimental Investigations ◽  
Polar Regions ◽  
Ionospheric Currents ◽  
Geomagnetic Variations ◽  
Activity Effect

Abstract. The equatorial ionosphere parameters, Kp, Dst, AU and AL indices characterized contribution of different magnetospheric and ionospheric currents to the H-component of geomagnetic field are examined to test the geomagnetic activity effect on the generation of ionospheric irregularities producing VLF scintillations. According to the results of the current statistical studies, one can predict near 70% of scintillations from Aarons' criteria using the Dst index, which mainly depicts the magnetospheric ring current field. To amplify Aarons' criteria or to propose new criteria for predicting scintillation characteristics is the question. In the present phase of the experimental investigations of electron density irregularities in the ionosphere new ways are opened up because observations in the interaction between the solar wind - magnetosphere - ionosphere during magnetic storms have progressed greatly. According to present view, the intensity of the electric fields and currents at the polar regions, as well as the magnetospheric ring current intensity, are strongly dependent on the variations of the interplanetary magnetic field. The magnetospheric ring current cannot directly penetrate the equatorial ionosphere and because of this difficulties emerge in explaining its relation to scintillation activity. On the other hand, the equatorial scintillations can be observed in the absence of the magnetospheric ring current. It is shown that in addition to Aarons' criteria for the prediction of the ionospheric scintillations, models can be used to explain the relationship between the equatorial ionospheric parameters, h'F, foF2, and the equatorial geomagnetic variations with the polar ionosphere currents and the solar wind.

scholarly journals The HIA instrument on board the Tan Ce 1 Double Star near-equatorial spacecraft and its first results

2005 ◽  
Vol 23 (8) ◽  
pp. 2757-2774 ◽  
Author(s):  
H. Rème ◽  
I. Dandouras ◽  
C. Aoustin ◽  
J. M. Bosqued ◽  
J. A. Sauvaud ◽  
...  
Keyword(s):  
Solar Wind ◽  
Ring Current ◽  
Geomagnetic Storms ◽  
Distribution Functions ◽  
Double Star ◽  
Magnetospheric Substorms ◽  
Scientific Cooperation ◽  
Low Latitude ◽  
First Results ◽  
Academy Of Sciences

Abstract. On 29 December 2003, the Chinese spacecraft Tan Ce 1 (TC-1), the first component of the Double Star mission, was successfully launched within a low-latitude eccentric orbit. In the framework of the scientific cooperation between the Academy of Sciences of China and ESA, several European instruments, identical to those developed for the Cluster spacecraft, were installed on board this spacecraft. The HIA (Hot Ion Analyzer) instrument on board the TC-1 spacecraft is an ion spectrometer nearly identical to the HIA sensor of the CIS instrument on board the 4 Cluster spacecraft. This instrument has been specially adapted for TC-1. It measures the 3-D distribution functions of the ions between 5 eV/q and 32 keV/q without mass discrimination. TC-1 is like a fifth Cluster spacecraft to study the interaction of the solar wind with the magnetosphere and to study geomagnetic storms and magnetospheric substorms in the near equatorial plane. HIA was commissioned in February 2004. Due to the 2 RE higher apogee than expected, some in-flight improvements were needed in order to use HIA in the solar wind in the initial phase of the mission. Since this period HIA has obtained very good measurements in the solar wind, the magnetosheath, the dayside and nightside plasma sheet, the ring current and the radiation belts. We present here the first results in the different regions of the magnetosphere and in the solar wind. Some of them are very new and include, for example, ion dispersion structures in the bow shock and ion beams close to the magnetopause. The huge interest in the orbit of TC-1 is strongly demonstrated.

scholarly journals Influences on the radius of the auroral oval

2009 ◽  
Vol 27 (7) ◽  
pp. 2913-2924 ◽  
Author(s):  
S. E. Milan ◽  
J. Hutchinson ◽  
P. D. Boakes ◽  
B. Hubert
Keyword(s):  
Solar Wind ◽  
Ring Current ◽  
Geomagnetic Storms ◽  
Auroral Oval ◽  
Substorm Onset ◽  
Polar Cap ◽  
H Index ◽  
Magnetic Perturbation

Abstract. We examine the variation in the radius of the auroral oval, as measured from auroral images gathered by the Imager for Magnetopause-to-Aurora Global Exploration (IMAGE) spacecraft, in response to solar wind inputs measured by the Advanced Composition Explorer (ACE) spacecraft for the two year interval June 2000 to May 2002. Our main finding is that the oval radius increases when the ring current, as measured by the Sym-H index, is intensified during geomagnetic storms. We discuss our findings within the context of the expanding/contracting polar cap paradigm, in terms of a modification of substorm onset conditions by the magnetic perturbation associated with the ring current.

scholarly journals Electron precipitation events in the lower ionosphere and the geospace conditions

2013 ◽  
Vol 56 (2) ◽  
Author(s):  
José Henrique Fernandez ◽  
Emília Correia
Keyword(s):  
Solar Wind ◽  
Geomagnetic Storms ◽  
Close Association ◽  
Low Frequency ◽  
Lower Ionosphere ◽  
Recovery Phase ◽  
Activity Level ◽  
23Rd Solar Cycle ◽  
Solar Wind Parameters ◽  
Precipitation Events

<p>We present an analysis of localized ionospheric perturbations detected at Comandante Ferraz Brazilian Antarctic Station (McIlwain parameter L~2.25) as fast-amplitude variations of very low frequency (VLF) signals transmitted from Hawaii (NPM, at 21.4 kHz), also known as Trimpi events. The study covers the first six months of 2007, during the period of minimum activity in the 23rd solar cycle. The occurrence of Trimpi events in the Antarctica peninsula region was studied in association with solar-wind parameters in the neighborhood of the Earth (geospace), along with the geomagnetic activity level (Ap, Dst indices). The analysis shows that the Trimpi events occurred predominantly during geomagnetically disturbed periods, but they have a more intricate association with the geospace regimes. The events achieve higher occurrence during the recovery phase of some geomagnetic storms, and also show a close association with electron flux enhancements in the belt region, especially those with higher energy. The higher event incidence occurred a few hours after what we call the 'angle bracket' phenomenon: when the solar wind velocity rises simultaneous with a decrease in its density.</p>

scholarly journals Relationship between geomagnetic storm development and the solar wind parameter ß

2021 ◽  
Vol 7 (4) ◽  
pp. 24-32
Author(s):  
Nadezhda Kurazhkovskaya ◽  
Oleg Zotov ◽  
Boris Klain
Keyword(s):  
Solar Wind ◽  
Geomagnetic Storms ◽  
Activity Cycle ◽  
Solar Activity Cycle ◽  
Solar Wind Plasma ◽  
Recovery Phase ◽  
Plasma Pressure ◽  
Superposition Method ◽  
Solar Wind Parameter ◽  
Dst Index

We have analyzed the dynamics of solar wind and interplanetary magnetic field (IMF) parameters during the development of 933 isolated geomagnetic storms, observed over the period from 1964 to 2010. The analysis was carried out using the epoch superposition method at intervals of 48 hrs before and 168 hrs after the moment of Dst minimum. The geomagnetic storms were selected by the type of storm commencement (sudden or gradual) and by intensity (weak, moderate, and strong). The dynamics of the solar wind and IMF parameters was compared with that of the Dst index, which is an indicator of the development of geomagnetic storms. The largest number of storms in the solar activity cycle is shown to occur in the years of minimum average values (close in magnitude to 1) of the solar wind parameter β (β is the ratio of plasma pressure to magnetic pressure). We have revealed that the dynamics of the Dst index is similar to that of the β parameter. The duration of the storm recovery phase follows the characteristic recovery time of the β parameter. We have found out that during the storm main phase the β parameter is close to 1, which reflects the maximum turbulence of solar wind plasma fluctuations. In the recovery phase, β returns to background values β~2‒3.5. We assume that the solar wind plasma turbulence, characterized by the β parameter, can play a significant role in the development of geomagnetic storms.

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