Echo state network model for analyzing solar-wind effects on the AU and AL indices

The properties of the auroral electrojets are examined on the basis of a trained machine-learning model. The relationships between solar-wind parameters and the AU and AL indices are modeled with an echo state network (ESN), a kind of recurrent neural network. We can consider this trained ESN model to represent nonlinear effects of the solar-wind inputs on the auroral electrojets. To identify the properties of auroral electrojets, we obtain various synthetic AU and AL data by using various artificial inputs with the trained ESN. The analyses of various synthetic data show that the AU and AL indices are mainly controlled by the solar-wind speed in addition to Bz of the interplanetary magnetic field (IMF) as suggested by the literature. The results also indicate that the solar-wind density effect is emphasized when solar-wind speed is high and when IMF Bz is near zero. This suggests some nonlinear effects of the solar-wind density.

Solar Wind Parameters and Its Geoefficiency During Minimums of Four Solar Cycles

Recently a number of publications have appeared on the long and deep minimum in cycle 23 of solar activity. This interest is due to the fact that it turned out to be the longest and deepest in terms of the number of sunspots in the entire era of space exploration. The features of the minimum of cycle 23 of solar activity and the beginning of cycle 24 made it possible to assume that in the coming decades, a minimum of solar activity similar to the Dalton or Maunder minimum, leading to a global change in the earth's climate, may occur. Such assumptions make a detailed study of the influence of the minimum of solar cycle 23 on the parameters of the solar wind and the interplanetary magnetic field, as well as a comparison of this influence with similar manifestations in the three previous cycles very urgent. The work carried out statistical processing and analysis of data available in print and on the Internet on the indices of solar activity (W and F10.7), on geomagnetic activity, as well as on the parameters of the solar wind and interplanetary field. In contrast to other similar studies, when choosing time intervals for all cycles, only one — 12 months was used, which made it possible to exclude annual and semi-annual variations in solar wind parameters. For the considered minima of solar activity, the geoeffectiveness of the disturbed fluxes ICME, CIR, and Sheath was considered. A monotonic and very significant decrease in the geoeffectiveness of the ICME streams was found. Data processing on the hourly average values of the solar wind parameters at the minima of geomagnetic activity for 4 cycles confirmed the significant difference between cycle 23 and the previous ones in the behavior of the magnetic field. The cycle-by-cycle decrease in the geoeffectiveness of coronal ejections discussed in the press deserves a more detailed analysis using extensive data on magnetic activity indices.

Earth’s geomagnetic response to solar wind changes associated with solar events at low latitude regions at the TRE MAGDAS Station

The Sun’s magnetic activity influences disturbances that perturb interplanetary space by producing large fluxes of energetic protons, triggering geomagnetic storms and affecting the ground geomagnetic field. The effect of two solar events, namely Coronal Mass Ejection (CME) and Coronal Holes, on geomagnetic indices (SYM/H), solar wind parameters and ground geomagnetic fields has provided magnetic ground data, which were extracted from the Terengganu (TRE, -4.21° N, 175.91° E) Magnetometer (MAGDAS) station, and investigated in this study. Results show that the physical dynamic mechanism in the Earth’s magnetosphere is triggered by various solar wind parameters associated with CMEs and Coronal hole events during the minimum solar cycle of 24 at low latitudes. It is important to study solar wind-magnetosphere coupling because it has an impact on ground-based technological systems and human activities.

A statistical analysis of the relationship between Pc4 and Pc5 ULF waves, solar winds and geomagnetic storms for predicting earthquake precursor signatures in low latitude regions

Short-term earthquake forecasting is impossible due to the seismometer’s limited sensitivity in detecting the generation of micro-fractures prior to an earthquake. Therefore, there is a strong desire for a non-seismological approach, and one of the most established methods is geomagnetic disturbance observation. Previous research shows that disturbances in the ground geomagnetic field serves as a potential precursor for earthquake studies. It was discovered that electromagnetic waves (EM) in the Ultra-Low Frequency (ULF) range are a promising tool for studying the seismomagnetic effect of earthquake precursors. This study used a multiple regression approach to analyse the preliminary study on the relationship between Pc4 (6.7-22 mHz) and Pc5 (1.7-6.7 mHz) ULF magnetic pulsations, solar wind parameters and geomagnetic indices for predicting earthquake precursor signatures in low latitude regions. The ground geomagnetic field was collected from Davao station (7.00° N, 125.40° E), in the Philippines, which experiences nearby earthquake events (Magnitude <5.0, depth <100 km and epicentre distance from magnetometer station <100 km). The Pc5 ULF waves show the highest variance with four solar wind parameters, namely SWS, SWP, IMF-Bz, SIE and geomagnetic indices (SYM/H) prior to an earthquake event based on the regression model value of R2 = 0.1510. Furthermore, the IMF-Bz, SWS, SWP, SWE, and SYM/H were found to be significantly correlated with Pc5 ULF geomagnetic pulsation. This Pc5 ULF magnetic pulsation behaviour in solar winds and geomagnetic storms establishes the possibility of using Pc5 to predict earthquakes.

Virtual sounding of solar-wind effects on the AU and AL indices based on an echo state network model

The properties of the auroral electrojets are examined on the basis of a trained machine learning model. The relationships between solar-wind parameters and the AU and AL indices are modeled with an echo state network (ESN), a kind of recurrent neural network. We can consider this trained ESN model to represent nonlinear effects of the solar-wind inputs on the auroral electrojets. To identify the properties of auroral electrojets, we obtain various synthetic AU and AL data by using various artificial inputs with the trained ESN. The analyses of various synthetic data show that the AU and AL indices are mainly controlled by the solar-wind speed in addition to Bz of the interplanetary magnetic field (IMF) as suggested by the literature. The results also indicate that the solar-wind density effect is emphasized when solar-wind speed is high and when IMF Bz is near zero. This suggests some nonlinear effects of the solar-wind density.

Mathematical Analysis of the 08 May 2014 Weak Storm

Since the time scale of weak storms is about half the time scale of intense storms, it is troublesome and important to examine the solar wind parameters/interplanetary magnetic field (IMF) (E, v , P , T, N, and Bz) to evolve and affect to zonal geomagnetic indices (Kp, Dst, AE, and ap). In a severe storm, which usually has two main phases, solar parameters have enough time to react, but weak storms cannot find this time. They have to yield their reaction in a short time. One can find a weak storm in order to reveal and discuss the consistency of models that have proven themselves in severe and moderate storms in this study. I discuss weak storm (Dst = −46) on May 8, 2014, via solar wind parameters and zonal geomagnetic indices. The goal of the work is to realize the models applicable to the moderate and the strong storms for a weak storm. Hereby, all possible correlations between solar parameters and zonal indices are discussed in depth. I tried to obey the cause-effect relationship while creating mathematical models while not ignoring the physical principles. Therefore, the physical principles govern the study. The results are visualized with tables and graphs for the understanding of the dynamic structure of the storm.

Evaluating the Accuracy of Magnetospheric Magnetic Field Models Using Cluster Spacecraft Magnetic Field Measurements

Magnetic fields in the inner magnetosphere can be obtained as vector sums of the Earth’s own internal magnetic field and magnetic fields stemming from currents flowing in the space plasma. While the Earth’s internal magnetic field is accurately described by the International Geomagnetic Reference Field (IGRF) model, the characterization of the external magnetic fields is significantly more complicated, as they are highly variable and dependent on the actual level of the geomagnetic activity. Tsyganenko family magnetic field models (T89, T96, T01, TA15B, TA15N), parameterized by the geomagnetic activity level and solar wind parameters, are often used by the involved community to describe these fields. In the present paper, we use a large dataset (2001–2018) of magnetospheric magnetic field measurements obtained by the four Cluster spacecraft to assess the accuracy of these models. We show that, while the newer models (T01, TA15B, TA15N) perform significantly better than the old ones (T89, T96), there remain some systematic deviations, in particular at larger latitudes. Moreover, we compare the locations of the min-B equator determined using the four-point Cluster spacecraft measurements with the locations determined using the magnetic field models. We demonstrate that, despite the newer models being comparatively slightly more accurate, an uncertainty of about one degree in the latitude of the min-B equator remains.

Variations in Energetic Particle Fluxes around Significant Geomagnetic Storms Observed by the Low-Altitude DEMETER Spacecraft

A superposed epoch analysis is conducted for five geomagnetic storms in the years 2005 and 2006 with the aim to understand energetic particle flux variations as a function of L-shell, energy and time from the Dst minimum. Data measured by the low-altitude DEMETER spacecraft were used for this purpose. The storms were identified by a Dst index below −100 nT, as well as their being isolated events in a seven-day time window. It is shown that they can be categorized into two types. The first type shows significant variations in the energetic particle fluxes around the Dst minimum and increased fluxes at high energies (>1.5 MeV), while the second type only shows increased fluxes around the Dst minimum without the increased fluxes at high energies. The first type of storm is related to more drastic but shorter-lasting changes in the solar wind parameters than the second type. One storm does not fit either category, exhibiting features from both storm types. Additionally, we investigate whether the impenetrable barrier for ultra-relativistic electrons also holds in extreme geomagnetic conditions. For the highest analyzed energies, the obtained barrier L-shells do not go below 2.6, consistent with previous findings.