Investigation of the Geoeffectiveness of Disk-Centre Full-Halo Coronal Mass Ejections

We studied the occurrence and characteristics of geomagnetic storms associated with disk-centre full-halo coronal mass ejections (DC-FH-CMEs). Such coronal mass ejections (CMEs) can be considered as the most plausible cause of geomagnetic storms. We selected front-side full-halo coronal mass ejections detected by the Large Angle and Spectrometric Coronagraph onboard the Solar and Heliospheric Observatory (SOHO/LASCO) from the beginning of 1996 till the end of 2015 with source locations between solar longitudes E10 and W10 and latitudes N20 and S20. The number of selected CMEs was 66 of which 33 (50%) were deduced to be the cause of 30 geomagnetic storms with \(\mathrm{Dst} \leq- 50~\mbox{nT}\). Of the 30 geomagnetic storms, 26 were associated with single disk-centre full-halo CMEs, while four storms were associated, in addition to at least one disk-centre full-halo CME, also with other halo or wide CMEs from the same active region. Thirteen of the 66 CMEs (20%) were associated with 13 storms with \(-100~\mbox{nT} < \mbox{Dst} \leq- 50~\mbox{nT}\), and 20 (30%) were associated with 17 storms with \(\mbox{Dst}\leq- 100~\mbox{nT}\). We investigated the distributions and average values of parameters describing the DC-FH-CMEs and their interplanetary counterparts encountering Earth. These parameters included the CME sky-plane speed and direction parameter, associated solar soft X-ray flux, interplanetary magnetic field strength, \(B_{t}\), southward component of the interplanetary magnetic field, \(B_{s}\), solar wind speed, \(V_{sw}\), and the \(y\)-component of the solar wind electric field, \(E_{y}\). We found only a weak correlation between the Dst of the geomagnetic storms associated with DC-FH-CMEs and the CME sky-plane speed and the CME direction parameter, while the correlation was strong between the Dst and all the solar wind parameters (\(B_{t}\), \(B_{s}\), \(V_{sw}\), \(E_{y}\)) measured at 1 AU. We investigated the dependences of the properties of DC-FH-CMEs and the associated geomagnetic storms on different phases of solar cycles and the differences between Solar Cycles 23 and 24. In the rise phase of Solar Cycle 23 (SC23), five out of eight DC-FH-CMEs were geoeffective (\(\mbox{Dst} \leq- 50~\mbox{nT}\)). In the corresponding phase of SC24, only four DC-FH-CMEs were observed, three of which were nongeoeffective (\(\mbox{Dst} > - 50~\mbox{nT}\)). The largest number of DC-FH-CMEs occurred at the maximum phases of the cycles (21 and 17, respectively). Most of the storms with \(\mbox{Dst}\leq- 100~\mbox{nT}\) occurred at or close to the maximum phases of the cycles. When comparing the storms during epochs of corresponding lengths in Solar Cycles 23 and 24, we found that during the first 85 months of Cycle 23 the geoeffectiveness rate of the disk-centre full-halo CMEs was 58% with an average minimum value of the Dst index of \(- 146~\mbox{nT}\). During the corresponding epoch of Cycle 24, only 35% of the disk-centre full-halo CMEs were geoeffective with an average value of Dst of \(- 97~\mbox{nT}\).     

Interplanetary Coronal Mass Ejections Resulting from Earth-Directed CMEs Using SOHO and ACE Combined Data During Solar Cycle 23

In this work a total of 266 interplanetary coronal mass ejections observed by the Solar and Heliospheric Observatory/Large Angle and Spectrometric Coronagraph (SOHO/LASCO) and then studied by in situ observations from Advanced Composition Explorer (ACE) spacecraft, are presented in a new catalog for the time interval 1996?–?2009 covering Solar Cycle 23. Specifically, we determine the characteristics of the CME which is responsible for the upcoming ICME and the associated solar flare, the initial/background solar wind plasma and magnetic field conditions before the arrival of the CME, the conditions in the sheath of the ICME, the main part of the ICME, the geomagnetic conditions of the ICME’s impact at Earth and finally we remark on the visual examination for each event. Interesting results revealed from this study include the high correlation coefficient values of the magnetic field \(B_{z}\) component against the Ap index (\(r = 0.84\)), as well as against the Dst index (\(r = 0.80\)) and of the effective acceleration against the CME linear speed (\(r = 0.98\)). We also identify a north–south asymmetry for X-class solar flares and an east–west asymmetry for CMEs associated with strong solar flares (magnitude ≥ M1.0) which finally triggered intense geomagnetic storms (with \(\mathrm{Ap} \geq179\)). The majority of the geomagnetic storms are determined to be due to the ICME main part and not to the extreme conditions which dominate inside the sheath. For the intense geomagnetic storms the maximum value of the Ap index is observed almost 4 hours before the minimum Dst index. The amount of information makes this new catalog the most comprehensive ICME catalog for Solar Cycle 23.     

Geomagnetic Effects of Corotating Interaction Regions

We present an analysis of the geoeffectiveness of corotating interaction regions (CIRs), employing the data recorded from 25 January to 5 May 2005 and throughout 2008. These two intervals in the declining phase of Solar Cycle 23 are characterised by a particularly low number of interplanetary coronal mass ejections (ICMEs). We study in detail how four geomagnetic-activity parameters (the Dst, Ap, and AE indices, as well as the Dst time derivative, \(\mathrm{dDst}/\mathrm{d}t\)) are related to three CIR-related solar wind parameters (flow speed, \(V\), magnetic field, \(B\), and the convective electric field based on the southward Geocentric solar magnetospheric (GSM) magnetic field component, \(\mathit{VB}_{s}\)) on a three-hour time resolution. In addition, we quantify statistical relationships between the mentioned geomagnetic indices. It is found that Dst is correlated best to \(V\), with a correlation coefficient of \(\mathrm{cc}\approx0.6\), whereas there is no correlation between \(\mathrm{dDst}/\mathrm{d}t\) and \(V\). The Ap and AE indices attain peaks about half a day before the maximum of \(V\), with correlation coefficients ranging from \(\mathrm{cc}\approx0.6\) to \(\mathrm{cc}\approx0.7\), depending on the sample used. The best correlations of Ap and AE are found with \(\mathit{VB}_{s}\) with a delay of 3 h, being characterised by \(\mathrm{cc}\gtrsim 0.6\). The Dst derivative \(\mathrm{dDst}/\mathrm{d}t\) is also correlated with \(\mathit{VB}_{s}\), but the correlation is significantly weaker \(\mathrm{cc}\approx 0.4\)?–?0.5, with a delay of 0?–?3 h, depending on the employed sample. Such low values of correlation coefficients indicate that there are other significant effects that influence the relationship between the considered parameters. The correlation of all studied geomagnetic parameters with \(B\) are characterised by considerably lower correlation coefficients, ranging from \(\mathrm{cc}=0.3\) in the case of \(\mathrm{dDst}/\mathrm{d}t\) up to \(\mathrm{cc}=0.56\) in the case of Ap. It is also shown that peak values of geomagnetic indices depend on the duration of the CIR-related structures. The Dst is closely correlated with Ap and AE (\(\mathrm{cc}=0.7\)), Dst being delayed for about 3 h. On the other hand, \(\mathrm{dDst}/\mathrm{d}t\) peaks simultaneously with Ap and AE, with correlation coefficients of 0.48 and 0.56, respectively. The highest correlation (\(\mathrm{cc}=0.81\)) is found for the relationship between Ap and AE.     

Temporal and Periodic Variations of Sunspot Counts in Flaring and Non-Flaring Active Regions

We analyzed temporal and periodic variations of sunspot counts (SSCs) in flaring (C-, M-, or X-class flares), and non-flaring active regions (ARs) for nearly three solar cycles (1986 through 2016). Our main findings are as follows: i) temporal variations of monthly means of the daily total SSCs in flaring and non-flaring ARs behave differently during a solar cycle and the behavior varies from one cycle to another; during Solar Cycle 23 temporal SSC profiles of non-flaring ARs are wider than those of flaring ARs, while they are almost the same during Solar Cycle 22 and the current Cycle 24. The SSC profiles show a multi-peak structure and the second peak of flaring ARs dominates the current Cycle 24, while the difference between peaks is less pronounced during Solar Cycles 22 and 23. The first and second SSC peaks of non-flaring ARs have comparable magnitude in the current solar cycle, while the first peak is nearly absent in the case of the flaring ARs of the same cycle. ii) Periodic variations observed in the SSCs profiles of flaring and non-flaring ARs derived from the multi-taper method (MTM) spectrum and wavelet scalograms are quite different as well, and they vary from one solar cycle to another. The largest detected period in flaring ARs is \(113\pm 1.6~\mbox{days}\) while we detected much longer periodicities (\(327\pm 13\), \(312 \pm 11\), and \(256\pm 8~\mbox{days}\)) in the non-flaring AR profiles. No meaningful periodicities were detected in the MTM spectrum of flaring ARs exceeding \(55\pm 0.7~\mbox{days}\) during Solar Cycles 22 and 24, while a \(113\pm 1.3~\mbox{days}\) period was detected in flaring ARs of Solar Cycle 23. For the non-flaring ARs the largest detected period was only \(31\pm 0.2~\mbox{days}\) for Cycle 22 and \(72\pm 1.3~\mbox{days}\) for the current Cycle 24, while the largest measured period was \(327\pm 13~\mbox{days}\) during Solar Cycle 23.     

GONG p-Mode Parameters Through Two Solar Cycles

We investigate the parameters of global solar p-mode oscillations, namely damping width \(\Gamma\), amplitude \(A\), mean squared velocity \(\langle v^{2}\rangle\), energy \(E\), and energy supply rate \(\mathrm{d}E/\mathrm{d}t\), derived from two solar cycles’ worth (1996?–?2018) of Global Oscillation Network Group (GONG) time series for harmonic degrees \(l=0\,\mbox{--}\,150\). We correct for the effect of fill factor, apparent solar radius, and spurious jumps in the mode amplitudes. We find that the amplitude of the activity-related changes of \(\Gamma\) and \(A\) depends on both frequency and harmonic degree of the modes, with the largest variations of \(\Gamma\) for modes with \(2400~\upmu\mbox{Hz}\le\nu\le3300~\upmu\mbox{Hz}\) and \(31\le l \le60\) with a minimum-to-maximum variation of \(26.6\pm0.3\%\) and of \(A\) for modes with \(2400~\upmu\mbox{Hz}\le\nu\le 3300~\upmu\mbox{Hz}\) and \(61\le l \le100\) with a minimum-to-maximum variation of \(27.4\pm0.4\%\). The level of correlation between the solar radio flux \(F_{10.7}\) and mode parameters also depends on mode frequency and harmonic degree. As a function of mode frequency, the mode amplitudes are found to follow an asymmetric Voigt profile with \(\nu_{\text{max}}=3073.59\pm0.18~\upmu\mbox{Hz}\). From the mode parameters, we calculate physical mode quantities and average them over specific mode frequency ranges. In this way, we find that the mean squared velocities \(\langle v^{2}\rangle\) and energies \(E\) of p modes are anticorrelated with the level of activity, varying by \(14.7\pm0.3\%\) and \(18.4\pm0.3\%\), respectively, and that the mode energy supply rates show no significant correlation with activity. With this study we expand previously published results on the temporal variation of solar p-mode parameters. Our results will be helpful to future studies of the excitation and damping of p modes, i.e., the interplay between convection, magnetic field, and resonant acoustic oscillations.     

Relation Between Coronal Hole Areas and Solar Wind Speeds Derived from Interplanetary Scintillation Measurements

We investigate the relation between coronal hole (CH) areas and solar wind speeds during 1995?–?2011 using the potential field (PF) model analysis of magnetograph observations and interplanetary scintillation (IPS) observations by the Institute for Space-Earth Environmental Research (formerly Solar-Terrestrial Environment Laboratory) of Nagoya University. We obtained a significant positive correlation between the CH areas (\(A\)) derived from the PF model calculations and solar wind speeds (\(V\)) derived from the IPS observations. The correlation coefficients between them are usually high, but they drop significantly in solar maxima. The slopes of the \(A\)?–?\(V\) relation are roughly constant except for the period around solar maximum, when flatter or steeper slopes are observed. The excursion of the correlation coefficients and slopes at solar maxima is ascribed partly to the effect of rapid structural changes in the coronal magnetic field and solar wind, and partly to the predominance of small CHs. It is also demonstrated that \(V\) is inversely related to the flux expansion factor (\(f\)) and that \(f\) is closely related to \(A^{-1/2}\); hence, \(V \propto A^{1/2}\). A better correlation coefficient is obtained from the \(A^{1/2}\)?–?\(V\) relation, and this fact is useful for improving space weather predictions. We compare the CH areas derived from the PF model calculations with He i 1083 nm observations and show that the PF model calculations provide reliable estimates of the CH area, particularly for large \(A\).     

An Early Prediction of the Amplitude of Solar Cycle 25

A “Solar Dynamo” (SODA) Index prediction of the amplitude of Solar Cycle 25 is described. The SODA Index combines values of the solar polar magnetic field and the solar spectral irradiance at 10.7 cm to create a precursor of future solar activity. The result is an envelope of solar activity that minimizes the 11-year period of the sunspot cycle. We show that the variation in time of the SODA Index is similar to several wavelet transforms of the solar spectral irradiance at 10.7 cm. Polar field predictions for Solar Cycles 21?–?24 are used to show the success of the polar field precursor in previous sunspot cycles. Using the present value of the SODA index, we estimate that the next cycle’s smoothed peak activity will be about \(140 \pm30\) solar flux units for the 10.7 cm radio flux and a Version 2 sunspot number of \(135 \pm25\). This suggests that Solar Cycle 25 will be comparable to Solar Cycle 24. The estimated peak is expected to occur near \(2025.2 \pm1.5\) year. Because the current approach uses data prior to solar minimum, these estimates may improve as the upcoming solar minimum draws closer.     

Intermittency of the Solar Magnetic Field and Solar Magnetic Activity Cycle

Small-scale solar magnetic fields demonstrate features of fractal intermittent behavior, which requires quantification. For this purpose we investigate how the observational estimate of the solar magnetic flux density \(B\) depends on resolution \(D\) in order to obtain the scaling \(\ln B_{D} = - k \ln D +a\) in a reasonably wide range. The quantity \(k\) demonstrates cyclic variations typical of a solar activity cycle. In addition, \(k\) depends on the magnetic flux density, i.e. the ratio of the magnetic flux to the area over which the flux is calculated, at a given instant. The quantity \(a\) demonstrates some cyclic variation, but it is much weaker than in the case of \(k\). The scaling obtained generalizes previous scalings found for the particular cycle phases. The scaling is typical of fractal structures. In our opinion, the results obtained trace small-scale action in the solar convective zone and its coexistence with the conventional large-scale solar dynamo based on differential rotation and mirror-asymmetric convection.     

Relating Solar Energetic Particle Event Fluences to Peak Intensities

Recently we (Kahler and Ling, Solar Phys.292, 59, 2017: KL) have shown that time–intensity profiles [\(I(t)\)] of 14 large solar energetic particle (SEP) events can be fitted with a simple two-parameter fit, the modified Weibull function, which is characterized by shape and scaling parameters [\(\alpha\) and \(\beta\)]. We now look for a simple correlation between an event peak energy intensity [\(I_{\mathrm{p}}\)] and the time integral of \(I(t)\) over the event duration: the fluence [\(F\)]. We first ask how the ratio of \(F/I_{\mathrm{p}}\) varies for the fits of the 14 KL events and then examine that ratio for three separate published statistical studies of SEP events in which both \(F\) and \(I_{\mathrm{p}}\) were measured for comparisons of those parameters with various solar-flare and coronal mass ejection (CME) parameters. The three studies included SEP energies from a 4?–?13 MeV band to \(E > 100~\mbox{MeV}\). Within each group of SEP events, we find a very robust correlation (\(\mathrm{CC} > 0.90\)) in log–log plots of \(F\)versus\(I_{\mathrm{p}}\) over four decades of \(I_{\mathrm{p}}\). The ratio increases from western to eastern longitudes. From the value of \(I_{\mathrm{p}}\) for a given event, \(F\) can be estimated to within a standard deviation of a factor of \({\leq}\,2\). Log–log plots of two studies are consistent with slopes of unity, but the third study shows plot slopes of \({<}\,1\) and decreasing with increasing energy for their four energy ranges from \(E > 10~\mbox{MeV}\) to \({>}\,100~\mbox{MeV}\). This difference is not explained.     

Corotating Shock Waves and the Solar-wind Source of Energetic Ion bundances: Power Laws in $$/Q$Q$

We find that element abundances in energetic ions accelerated by shock waves formed at corotating interaction regions (CIRs) mirror the abundances of the solar wind modified by a decreasing power-law dependence on the mass-to-charge ratio \(A\)/\(Q\) of the ions. This behavior is similar in character to the well-known power-law dependence on \(A\)/\(Q\) of abundances in large gradual solar energetic particles (SEP). The CIR ions reflect the pattern of \(A\)/\(Q\), with \(Q\) values of the source plasma temperature or freezing-in temperature of 1.0?–?1.2 MK typical of the fast solar wind in this case. Thus the relative ion abundances in CIRs are of the form \((A\mbox{/}Q)^{a}\), where \(a\) is nearly always negative and evidently decreases with distance from the shocks, which usually begin beyond 1 AU. For one unusual historic CIR event where \(a \approx 0\), the reverse shock wave of the CIR seems to occur at 1 AU, and these abundances of the energetic ions become a direct proxy for the abundances of the fast solar wind.     

Dependence of the Sunspot-Group Size on the Level of Solar Activity and its Influence on the Calibration of Solar Observers

We study the distribution of the sunspot-group size (area) and its dependence on the level of solar activity. We show that the fraction of small groups is not constant but decreases with the level of solar activity so that high solar activity is mainly defined by large groups. We analyze the possible influence of solar activity on the ability of a realistic observer to see and report the daily number of sunspot groups. It is shown that the relation between the number of sunspot groups as seen by different observers with different observational acuity thresholds is strongly nonlinear and cannot be approximated by the traditionally used linear scaling (\(k\)-factors). The observational acuity threshold [\(A_{\mathrm{th}}\)] is considered to quantify the quality of each observer, instead of the traditional relative \(k\)-factor. A nonlinear \(c\)-factor based on \(A_{\mathrm{th}}\) is proposed, which can be used to correct each observer to the reference conditions. The method is tested on a pair of principal solar observers, Wolf and Wolfer, and it is shown that the traditional linear correction, with the constant \(k\)-factor of 1.66 to scale Wolf to Wolfer, leads to an overestimate of solar activity around solar maxima.     

Toward Spectroscopically Detecting the Global Latitudinal Temperature Variation on the Solar Surface

A very slight rotation-induced latitudinal temperature variation (presumably on the order of several kelvin) on the solar surface is theoretically expected. While recent high-precision solar brightness observations reported its detection, confirmation by an alternative approach using the strengths of spectral lines is desirable, for which reducing the noise due to random fluctuation caused by atmospheric inhomogeneity is critical. Toward this difficult task, we carried out a pilot study of spectroscopically investigating the relative variation of temperature (\(T\)) at a number of points in the solar circumference region near to the limb (where latitude dependence should be detectable, if any exists) based on the equivalent widths (\(W\)) of 28 selected lines in the 5367?–?5393 Å and 6075?–?6100 Å regions. We paid special attention to i) clarifying which types of lines should be employed and ii) how much precision is attainable in practice. We found that lines with strong \(T\)-sensitivity (\(|\log W/\log T|\)) should be used and that very weak lines should be avoided because they inevitably suffer strong relative fluctuations (\(\Delta W/W\)). Our analysis revealed that a precision of \(\Delta T/T \approx 0.003\) (corresponding to ≈?15 K) can be achieved at best by a spectral line with comparatively large \(|\log W/\log T|\), although this can possibly be further improved When a number of lines are used all together. Accordingly, if many such favorable lines could be measured with subpercent precision of \(\Delta W/W\) and by averaging the resulting \(\Delta T/T\) from each line, the random noise would eventually be reduced to ??1 K and detection of a very subtle amount of global \(T\)-gradient might be possible.     

Fourier Power Spectra of Solar Noise Storms

We analyzed three noise storms recorded on 200?–?400 MHz Trieste Callisto radio spectra on 2 July 2012, 8 July 2012, and 16 July 2012 by the Fourier method. We divided intervals of the noise storms into five-minute intervals, and in these intervals we computed the mean Fourier spectra as a function of the wave numbers in the frequency and height-scale spaces. We found that these Fourier spectra, where the spectrum from the quiet-activity interval was subtracted, are power-law spectra. The mean power-law index of these spectra in the range \(\ln(k_{z}) = [1.8, 2.9]\) (where \(k_{z}\) is the wave number in the height-scale space) is \(-1.7\pm0.14\), \(-1.6\pm0.14\), and \(-1.5 \pm0.12\) for the 2 July 2012, the 8 July 2012, and the 16 July 2012 noise storms, respectively. It appears that as the number of Type-I bursts in the studied interval increases, the power-law index becomes closer to \(-5/3\); this is known as the Kolmogorov spectral index. The power-law index of the noise storms is very similar to that of the narrowband dm-spikes found in our previous studies. Furthermore, we found a break in the power spectra at \(\ln(k_{z}) \approx2.9\), and the mean power-law index values above this break are \(-2.9\pm0.46\), \(-3.1\pm0.65\), and \(-3.4\pm0.98\), respectively.     

Spatial Distribution of Element Abundances and Ionization States in Solar Energetic-Particle Events

We have studied the spatial and temporal distribution of abundances of chemical elements in large “gradual” solar energetic-particle (SEP) events, and especially the source plasma temperatures, derived from those abundances, using measurements from the Wind and Solar TErrestrial RElations Observatory (STEREO) spacecraft, widely separated in solar longitude. A power-law relationship between abundance enhancements and mass-to-charge ratios [\(A/Q\)] of the ions can be used to determine \(Q\)-values and source plasma temperatures at remote spacecraft with instruments that were not designed for charge-state measurements. We search for possible source variations along the accelerating shock wave, finding one clear case where the accelerating shock wave appears to dispatch ions from \(3.2\pm 0.8~\mbox{MK}\) plasma toward one spacecraft and those from \(1.6\pm 0.2~\mbox{MK}\) plasma toward another, 116^° away. The difference persists for three days and then fades away. Three other SEP events show less-extreme variation in source temperatures at different spacecraft, in one case observed over 222^° in longitude. This initial study shows how the power-law relation between abundance enhancements and ion \(A/Q\)-values provides a new technique to determine \(Q\) and plasma temperatures in the seed population of SEP ions over a broad region of space using remote spacecraft with instruments that were not originally designed for measurements of ionization states.     

Prediction of the Length of Upcoming Solar Cycles

The forecast of solar cycle (SC) characteristics is crucial particularly for several space-based missions. In the present study, we propose a new model for predicting the length of the SC. The model uses the information of the width of an autocorrelation function that is derived from the daily sunspot data for each SC. We tested the model on Versions 1 and 2 of the daily international sunspot number data for SCs 10?–?24. We found that the autocorrelation width \(A_{\mathrm{w}} ^{n}\) of SC \(n\) during the second half of its ascending phase correlates well with the modified length that is defined as \(T_{\mathrm{cy}}^{n+2} - T_{\mathrm{a}}^{n}\). Here \(T_{\mathrm{cy}}^{n+2}\) and \(T_{ \mathrm{a}}^{n}\) are the length and ascent time of SCs \(n+2\) and \(n\), respectively. The estimated correlation coefficient between the model parameters is 0.93 (0.91) for Version 1 (Version 2) sunspot series. The standard errors in the observed and predicted lengths of the SCs for Version 1 and Version 2 data are 0.38 and 0.44 years, respectively. The advantage of the proposed model is that the predictions of the length of the upcoming two SCs (i.e., \(n+1\), \(n+2\)) are readily available at the time of the peak of SC \(n\). The present model gives a forecast of 11.01, 10.52, and 11.91 years (11.01, 12.20, and 11.68 years) for the length of SCs 24, 25, and 26, respectively, for Version 1 (Version 2).     

Nowcasting Solar Energetic Particle Events Using Principal Component Analysis

We perform a principal component analysis (PCA) on a set of six solar variables (i.e. width/size (\(s\)) and velocity (\(u\)) of a coronal mass ejection, logarithm of the solar flare (SF) magnitude (\(\log\mathit{SXRs}\)), SF longitude (\(\mathit{lon}\)), duration (\(\mathit{DT}\)), and rise time (\(\mathit{RT}\))). We classify the solar energetic particle (SEP) event radiation impact (in terms of the National Oceanic and Atmospheric Administration scales) with respect to the characteristics of their parent solar events. We further attempt to infer the possible prediction of SEP events. In our analysis, we use 126 SEP events with complete solar information, from 1997 to 2013. Each SEP event is a vector in six dimensions (corresponding to the six solar variables used in this work). The PCA transforms the input vectors into a set of orthogonal components. By mapping the characteristics of the parent solar events, a new base defined by these components led to the classification of the SEP events. We furthermore applied logistic regression analysis with single, as well as multiple explanatory variables, in order to develop a new index (\(I\)) for the nowcasting (short-term forecasting) of SEP events. We tested several different schemes for \(I\) and validated our findings with the implementation of categorical scores (probability of detection (POD) and false-alarm rate (FAR)). We present and interpret the obtained scores, and discuss the strengths and weaknesses of the different implementations. We show that \(I\) holds prognosis potential for SEP events. The maximum POD achieved is 77.78% and the relative FAR is 40.96%.     

Correlation Between the Magnetic Field and Plasma Parameters at 1 AU

The physical parameters of the solar wind observed in-situ near 1 AU have been studied for several decades, and relationships between them, such as the positive correlation between the solar wind plasma temperature, \(T\), and velocity, \(V\), and the negative correlation between density, \(N\), and velocity, \(V\), are well known. However, the magnetic field intensity, \(B\), does not appear to be well correlated with any individual plasma parameter. In this article, we discuss previously under-reported correlations between \(B\) and the combined plasma parameters \(\sqrt{N V^{2}} \) as well as between \(B\) and \(\sqrt{NT}\). These two correlations are strong during periods of corotating interaction regions and high-speed streams, and moderate during intervals of slow solar wind. The results indicate that the magnetic pressure in the solar wind is well correlated both with the plasma dynamic pressure and the thermal pressure.     

A study of the geomagnetic indices asymmetry based on the interplanetary magnetic field polarities

Data of geomagnetic indices (aa, Kp, Ap, and Dst) recorded near 1 AU over the period 1967–2016, have been studied based on the asymmetry between the interplanetary magnetic field (IMF) directions above and below of the heliospheric current sheet (HCS). Our results led to the following conclusions: (i) Throughout the considered period, 31 random years (62%) showed apparent asymmetries between Toward (\(\mathbf{T}\)) and Away (\(\mathbf{A}\)) polarity days and 19 years (38%) exhibited nearly a symmetrical behavior. The days of \(\mathbf{A}\) polarity predominated over the \(\mathbf{T}\) polarity days by 4.3% during the positive magnetic polarity epoch (1991–1999). While the days of \(\mathbf{T}\) polarity exceeded the days of \(\mathbf{A}\) polarity by 5.8% during the negative magnetic polarity epoch (2001–2012). (ii) Considerable yearly North–South (N–S) asymmetries of geomagnetic indices observed throughout the considered period. (iii) The largest toward dominant peaks for \(aa\) and \(Ap\) indices occurred in 1995 near to minimum of solar activity. Moreover, the most substantial away dominant peaks for \(aa\) and \(Ap\) indices occurred in 2003 (during the descending phase of the solar cycle 23) and in 1991 (near the maximum of solar activity cycle) respectively. (iv) The N–S asymmetry of \(Kp\) index indicated a most significant away dominant peak occurred in 2003. (v) Four of the away dominant peaks of Dst index occurred at the maxima of solar activity in the years 1980, 1990, 2000, and 2013. The largest toward dominant peak occurred in 1991 (at the reversal of IMF polarity). (vi) The geomagnetic indices (aa, Ap, and \(Kp\)) all have northern dominance during positive magnetic polarity epoch (1971–1979), while the asymmetries shifts to the southern solar hemisphere during negative magnetic polarity epoch (2001–2012).     

A comparative study of geomagnetic storms for solar cycles 23 and 24

The aim of this paper is to investigate the association of the geomagnetic storms with the magnitude of interplanetary magnetic field IMF (B), solar wind speed (V), product of IMF and wind speed (\(V \cdot B)\), Ap index and solar wind plasma density (\(n_{\mathrm{p}})\) for solar cycles 23 and 24. A Chree analysis by the superposed epoch method has been done for the study. The results of the present analysis showed that \(V \cdot B\) is more geoeffective when compared to V or B alone. Further the high and equal anti-correlation coefficient is found between Dst and Ap index (? 0.7) for both the solar cycles. We have also discussed the relationship between solar wind plasma density (\(n_{\mathrm{p}})\) and Dst and found that both these parameters are weakly correlated with each other. We have found that the occurrence of geomagnetic storms happens on the same day when IMF, V, Ap and \(V \cdot B\) reach their maximum value while 1 day time lag is noticed in case of solar wind plasma density with few exceptions. The study of geomagnetic storms with various solar-interplanetary parameters is useful for the study of space weather phenomenon.     

Effects of Geometries and Substructures of ICMEs on Geomagnetic Storms

To better understand geomagnetic storm generations by ICMEs, we consider the effect of substructures (magnetic cloud, MC, and sheath) and geometries (impact location of flux-rope at the Earth) of the ICMEs. We apply the toroidal magnetic flux-rope model to 59 CDAW CME–ICME pairs to identify their substructures and geometries, and select 20 MC-associated and five sheath-associated storm events. We investigate the relationship between the storm strength indicated by minimum Dst index \((\mathrm{Dst}_{\mathrm{min}})\) and solar wind conditions related to a southward magnetic field. We find that all slopes of linear regression lines for sheath-storm events are steeper (\({\geq}\,1.4\)) than those of the MC-storm events in the relationship between \(\mathrm{Dst}_{\mathrm{min}}\) and solar wind conditions, implying that the efficiency of sheath for the process of geomagnetic storm generations is higher than that of MC. These results suggest that different general solar wind conditions (sheaths have a higher density, dynamic and thermal pressures with a higher fluctuation of the parameters and higher magnetic fields than MCs) have different impact on storm generation. Regarding the geometric encounter of ICMEs, 100% (2/2) of major storms (\(\mathrm{Dst}_{\mathrm{min}} \leq -100~\mbox{nT}\)) occur in the regions at negative \(P_{Y}\) (relative position of the Earth trajectory from the ICME axis in the \(Y\) component of the GSE coordinate) when the eastern flanks of ICMEs encounter the Earth. We find similar statistical trends in solar wind conditions, suggesting that the dependence of geomagnetic storms on 3D ICME–Earth impact geometries is caused by asymmetric distributions of the geoeffective solar wind conditions. For western flank events, 80% (4/5) of the major storms occur in positive \(P_{Y}\) regions, while intense geoeffective solar wind conditions are not located in the positive \(P_{Y}\). These results suggest that the strength of geomagnetic storms depends on ICME–Earth impact geometries as they determine the solar wind conditions at Earth.