Geomagnetism and Aeronomy最新文献

Determining the speed of the solar wind emanating from coronal holes near the Sun is a key problem for modeling plasma parameters throughout the heliosphere. Plasma temperature and density, in addition to speed, are the input parameters to global magnetohydrodynamics models, but the estimated temperature and density boundary conditions are calculated from the simulated solar wind speed. In this study, we analyzed how long-term variations in the properties of open magnetic field sources modeled from different series of magnetograph observations are related to the plasma parameters measured by satellite. The analysis also considers coronal holes based on SDO/AIA 193 Å and solar wind speed observations in the Wang-Sheeley-Arge approximation (WSA). We found that during the period 2015–2023, the areas of equatorial coronal holes correlate better with the observed solar wind speed than the results of WSA simulations. Among the three considered series of magnetographic observations (STOP, SDO/HMI, GONG), during the period of minimum solar activity, calculations based on STOP data perform better.

In the paper, we examine the α inclination of the magnetic field of sunspots relative to the vertical. To determine the deviation angle α, a method to search for differences in the maximum of the longitudinal component of the magnetic field at various distances of spots from the central meridian in the eastern and western hemispheres of the Sun was used. Particular attention has been paid to the difference in the angles α for spots of leading and tail polarity of the magnetic field. Deviation angles α were shown to depend on the logarithm of the area while the dependences have opposite signs: α_L = 0.45°(±0.5) + 2.085°(±0.5) log S, (r = 0.95) for nuclei of leading polarity spots (L) and α_T = 5.43°(±1.0) – 3.95°(±0.7) log S, (r = 0.93) for nuclei of tail polarity (T). Here, the deviation of magnetic fields to the western limb is taken as a positive value. The found dependencies indicate the ascent of U-shaped force tubes.

The structure of the quasi-perpendicular bow shock of the Earth observed by the MMS spacecraft on 31 January 2017 with an Alfvén Mach number of approximately 10 and plasma parameter β of approximately 3, has been simulated using the Maximus hybrid kinetic code. We investigated types of instabilities governing the front structure and showed that in this case both ion Weibel and Alfvén ion cyclotron instabilities can arise at the shock foot simultaneously, thus leading to fast magnetic oscillations with a relative variation close to unity. Some signatures of the mirror instability were found in the near downstream. Simulation also showed that the front structure substantially differ for shock inclination angles of 50° and 75°.

The maximum energy of a solar flare is found using a model of particle acceleration in a magnetic X-singularity. Based on a comparison of this model with observed extreme events, it was determined that flares with the highest possible energy have already been observed. These include events of 1859, 1940, 2003, which had an X-ray class of X40 ± 5 (according to the GOES classification). In this case, the maximum flare energy in the modern era does not exceed 5 × 10³² erg, and such powerful flares occur at intervals of about 70 years.

In this paper, the dynamics of loop-like structures and related phenomena during the solar flare on February 24, 2023 are investigated. A new character of the dynamics of the coronal loop system during the flare has been studied, consisting in compression (lowering) of the loops both during the growth and decay phases of the flare. It was found that a sharp decrease in height began with the appearance of intense nonstationary plasma fluxes (ejections) observed mainly in the vicinity of the eastern footpoints of the coronal loop system. It was concluded that the rapid (at a speed of up to 25 km/s) compression of the coronal loop system can be explained by a decrease in free magnetic energy (a decrease in the vortex phi-component of the magnetic field) caused by the observed non-stationary plasma eruptions from the vicinity of the loops, as well as possible Joule dissipation of electric currents in the loops.

We present the results of a statistical study of the characteristics of active regions (ARs) and ribbons associated with flares of GOES class M5.0 and larger, occurring from February 2011 to December 2022 within 40° of the central meridian. A total of 60 flares met these criteria, of which 39 were eruptive and 21 confined. We used SDO/HMI and SDO/AIA data to obtain the magnetic reconnection fluxes and rates. Magnetic reconnection fluxes and ribbon areas of confined and eruptive flares correlate with the flares GOES class. For flares of the same GOES class in confined events, compared to eruptive ones, the mean magnetic flux density in the ribbon is higher. Reconnection rates in confined and eruptive flares showed a temporal evolution similar to observed hard X-ray (HXR) emission. The fraction of AR involved in reconnection is larger in eruptive flares and for both types of events it decreases with increasing distance between the flare and the AR center. For the same fraction of AR involved in the flare, eruptive events, compared to confined ones, are located at distances twice as far from the AR center. Eruptive flares tend to occur in compact ARs at the periphery, while confined ones occur in extended ARs near the center.

The seismo-electromagnetic studies have been in progress since 1998 at Agra station. In the present paper, ionospheric GPS-TEC, ground-based ULF/VLF measurements were investigated in light of four strong earthquakes (M ≥ 6.8) that occurred around the Indian subcontinent in different periods. These three datasets are processed by using advanced signal-processing techniques in time and frequency domains. To analyze these datasets, a period of 16 days (including the day of the earthquake) was considered. For each day, only one minute of data was taken into account, with the time of the earthquake being the midpoint of that minute. The precursors are obtained in all the datasets considered before the occurrence of earthquakes. In TEC, ULF, and VLF data, significant changes are observed 2 to 15, 2 to 7, and 5 to 13 days before earthquakes, respectively. Significant results are obtained in time and frequency domains and the variations of solar and magnetic storm activities have also been examined thoroughly to check the validity of these variations. Further, these variations are interpreted in terms of lithosphere-atmosphere-ionosphere coupling mechanisms available in the literature.

The occurrence of geomagnetic storms and the variation in the geomagnetic storm indices during the ascending phase of solar cycle 24 has been examined. The parameters considered for this study includes; IMF Bz (nT), solar wind speed (({{{v}}_{x}}), in km/s), Dst index (nT), Aurora Electroject (AE, AU and AL indices in nT), and sunspot number. The datasets span from 2010 to 2012. Results of the study reveals that; the frequency of occurrence of geomagnetic storms increases with the increase in solar activity. Six (6) geomagnetic storms were recorded in 2010 (with sunspot number, Rz = 16.5), 13 storms in 2012 (with sunspot number Rz = 55.7), and 17 storms occurred in 2012 (with sunspot number, Rz = 57.5) giving a total of 36 geomagnetic storm events for the entire period. The performed study demonstrates that an increase in the speed and density of the solar wind coincided with the decrease in the Dst index in 58% cases (in 21 out of 36 geomagnetic storms). However, in some cases, there was a sharp simultaneous increase in both the speed and density of the solar wind that fell on the recovery phase of the storm. This also in most cases coincided with the sharp north-south fluctuations in the IMF Bz. These variations cannot be unconnected with the nature of the drivers of such geomagnetic storms. It is evident that the behavior of the solar wind speed during geomagnetic storm events can provide meaningful insight on the underlying mechanisms and processes that drive the geomagnetic storm.

This study investigates Pc5 pulsations during the St. Patrick’s Day geomagnetic storm of March 17, 2015, using ground-based magnetic data from the SER station in Chile (29.827° S, 71.261° W), satellite observations, and geomagnetic indices. Pc5 pulsations, with frequencies of 1.67–6.67 mHz, are influenced by various factors, including the Kelvin–Helmholtz instability, field line resonance effects, and solar wind dynamics. During this storm ignificant variations in solar wind parameters were observed, with positive correlations between Pc5 pulsations and parameters like temperature, density, speed, and pressure, especially during the main and recovery phases Pc5 pulsations exhibited large amplitudes during the storm, potentially driven by magnetospheric MHD waveguide/cavity mode and induced by the substantial compression of the geomagnetic field from the solar wind. Our results show the appearance of Pc5 pulsations at low latitudes and strong correlations between solar wind parameters and Pc5 signals during all storm phases, with maximum correlation coefficients of 0.98.

The article considers the period from September 4 to September 10, 2017, inclusive, during which the last proton events of solar cycle 24 occurred. In order to detect possible additional proton sources and verify the sources already listed in various catalogs, we apply an empirical method for predicting proton events to all solar flares detected during this period. It is based on the threshold criteria of the parent flares. In addition, we apply an algorithm for automatic search of proton flares obtained by machine learning. Two variants of the automatic search algorithm are used: the first one (method 319) does not take into account the duration of the radio emission, while the second one (method 189) imposes a condition on its duration (>2 min). The empirical method shows that, except for the source flares found by the time of the first arrival of solar protons on Earth, other flares of this period do not fulfill all the criteria of “protonicity.” An additional test of the automatic method is the detection of proton flares that we selected by the protonicity criteria but that did not make it to the training sample. Method 319 considers proton flares X9.3 on September 6, 2017, M1.4 and X1.3 on September 7, 2017, and C8.3 on September 8, 2017, as proton flares. Method 189 does not consider the flares of September 7 and 8, 2017, as credible proton sources, which is consistent with expert empirical estimates of the protonicity criteria.