Active Region Photospheric Magnetic Properties Derived from Line-of-Sight and Radial Fields

The effect of using two representations of the normal-to-surface magnetic field to calculate photospheric measures that are related to the active region (AR) potential for flaring is presented. Several AR properties were computed using line-of-sight (\(B_{\mathrm{los}}\)) and spherical-radial (\(B_{r}\)) magnetograms from the Space-weather HMI Active Region Patch (SHARP) products of the Solar Dynamics Observatory, characterizing the presence and features of magnetic polarity inversion lines, fractality, and magnetic connectivity of the AR photospheric field. The data analyzed correspond to \({\approx\,}4{,}000\) AR observations, achieved by randomly selecting 25% of days between September 2012 and May 2016 for analysis at 6-hr cadence. Results from this statistical study include: i) the \(B_{r}\) component results in a slight upwards shift of property values in a manner consistent with a field-strength underestimation by the \(B_{\mathrm{los}}\) component; ii) using the \(B_{r}\) component results in significantly lower inter-property correlation in one-third of the cases, implying more independent information as regards the state of the AR photospheric magnetic field; iii) flaring rates for each property vary between the field components in a manner consistent with the differences in property-value ranges resulting from the components; iv) flaring rates generally increase for higher values of properties, except the Fourier spectral power index that has flare rates peaking around a value of \(5/3\). These findings indicate that there may be advantages in using \(B_{r}\) rather than \(B_{\mathrm{los}}\) in calculating flare-related AR magnetic properties, especially for regions located far from central meridian.     

Contribution to the Solar Mean Magnetic Field from Different Solar Regions

Seven-year-long seeing-free observations of solar magnetic fields with the Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamics Observatory (SDO) were used to study the sources of the solar mean magnetic field, SMMF, defined as the net line-of-sight magnetic flux divided over the solar disk area. To evaluate the contribution of different regions to the SMMF, we separated all the pixels of each SDO/HMI magnetogram into three subsets: weak (\(B^{\mathrm{W}}\)), intermediate (\(B^{\mathrm{I}}\)), and strong (\(B^{\mathrm{S}}\)) fields. The \(B^{\mathrm{W}}\) component represents areas with magnetic flux densities below the chosen threshold; the \(B^{\mathrm{I}}\) component is mainly represented by network fields, remains of decayed active regions (ARs), and ephemeral regions. The \(B^{\mathrm{S}}\) component consists of magnetic elements in ARs. To derive the contribution of a subset to the total SMMF, the linear regression coefficients between the corresponding component and the SMMF were calculated. We found that i) when the threshold level of 30 Mx?cm^?2 is applied, the \(B^{\mathrm{I}}\) and \(B^{\mathrm{S}}\) components together contribute from 65% to 95% of the SMMF, while the fraction of the occupied area varies in a range of 2?–?6% of the disk area; ii) as the threshold magnitude is lowered to 6 Mx?cm^?2, the contribution from \(B^{\mathrm{I}}+B^{\mathrm{S}}\) grows to 98%, and the fraction of the occupied area reaches a value of about 40% of the solar disk. In summary, we found that regardless of the threshold level, only a small part of the solar disk area contributes to the SMMF. This means that the photospheric magnetic structure is an intermittent inherently porous medium, resembling a percolation cluster. These findings suggest that the long-standing concept that continuous vast unipolar areas on the solar surface are the source of the SMMF may need to be reconsidered.     

The Na <Emphasis Type="SmallCaps">i</Emphasis> and Sr <Emphasis Type="SmallCaps">ii</Emphasis> Resonance Lines in Solar Prominences

We estimate the electron density, \(n_{\mathrm{e}}\), and its spatial variation in quiescent prominences from the observed emission ratio of the resonance lines Na?i?5890 Å (D₂) and Sr?ii?4078 Å. For a bright prominence (\(\tau_{\alpha}\approx25\)) we obtain a mean \(n_{\mathrm{e}}\approx2\times10^{10}~\mbox{cm}^{-3}\); for a faint one (\(\tau _{\alpha }\approx4\)) \(n_{\mathrm{e}}\approx4\times10^{10}~\mbox{cm}^{-3}\) on two consecutive days with moderate internal fluctuation and no systematic variation with height above the solar limb. The thermal and non-thermal contributions to the line broadening, \(T_{\mathrm{kin}}\) and \(V_{\mathrm{nth}}\), required to deduce \(n_{\mathrm{e}}\) from the emission ratio Na?i/Sr?ii cannot be unambiguously determined from observed widths of lines from atoms of different mass. The reduced widths, \(\Delta\lambda_{\mathrm{D}}/\lambda_{0}\), of Sr?ii?4078 Å show an excess over those from Na?D₂ and \(\mbox{H}\delta\,4101\) Å, assuming the same \(T_{\mathrm{kin}}\) and \(V_{\mathrm{nth}}\). We attribute this excess broadening to higher non-thermal broadening induced by interaction of ions with the prominence magnetic field. This is suggested by the finding of higher macro-shifts of Sr?ii?4078 Å as compared to those from Na?D₂.     

Determination of the Coronal and Interplanetary Magnetic Field Strength and Radial Profiles from Large-Scale Photospheric Magnetic Fields

We propose a new model for the magnetic field at different distances from the Sun during different phases of the solar cycle. The model depends on the observed large-scale non-polar (\({\pm}\, 55^{\circ }\)) photospheric magnetic field and on the magnetic field measured at polar regions from \(55^{\circ }\) N to \(90^{\circ }\) N and from \(55^{\circ }\) S to \(90^{\circ }\) S, which are the visible manifestations of cyclic changes in the toroidal and poloidal components of the global magnetic field of the Sun. The modeled magnetic field is determined as the superposition of the non-polar and polar photospheric magnetic field and considers cycle variations. The agreement between the model predictions and magnetic fields derived from direct in situ measurements at different distances from the Sun, obtained with different methods and at different solar activity phases, is quite satisfactory. From a comparison of the magnetic fields as observed and calculated from the model at 1 AU, we conclude that the model magnetic field variations adequately explain the main features of the interplanetary magnetic field (IMF) radial, \(B_{\mathrm{x}}\), component cycle evolution at Earth’s orbit. The modeled magnetic field averaged over a Carrington rotation (CR) correlates with the IMF \(B_{\mathrm{x}}\) component also averaged over a CR at Earth’s orbit with a coefficient of 0.691, while for seven CR-averaged data, the correlation reaches 0.81. The radial profiles of the modeled magnetic field are compared with those of already existing models. In contrast to existing models, ours provides realistic magnetic-field radial distributions over a wide range of heliospheric distances at different cycle phases, taking into account the cycle variations of the solar toroidal and poloidal magnetic fields. The model is a good approximation of the cycle behavior of the magnetic field in the heliosphere. In addition, the decrease in the non-polar and polar photospheric magnetic fields is shown. Furthermore, the magnetic field during solar cycle maxima and minima decreased from Cycle 21 to Cycle 24. This implies that both the toroidal and poloidal components, and therefore the solar global magnetic field, decreased from Cycle 21 to Cycle 24.     

Ratio of the Core to the Extended Emissions in the Comoving Frame for Blazars

In a two-component jet model, the emissions are the sum of the core and extended emissions: \(S^{\mathrm{ob}}=S_{\mathrm{core}}^{\mathrm{ob}}+S_{\mathrm{ext}}^{\mathrm{ob}}\), with the core emissions, \(S_{\mathrm{core}}^{\mathrm{ob}}= f S_{\mathrm{ext}}^{\mathrm{ob}}\delta ^{q}\) being a function of the Doppler factor \(\delta \), the extended emission \(S_{\mathrm{ext}}^{\mathrm{ob}}\), the jet type dependent factor q, and the ratio of the core to the extended emissions in the comoving frame, f. The f is an unobservable but important parameter. Following our previous work, we collect 65 blazars with available Doppler factor \(\delta \), superluminal velocity \(\beta _{\mathrm{app}}\), and core-dominance parameter, R, and calculated the ratio, f, and performed statistical analyses. We found that the ratio, f, in BL Lacs is on average larger than that in FSRQs. We suggest that the difference of the ratio f between FSRQs and BL Lacs is one of the possible reasons that cause the difference of other observed properties between them. We also find some significant correlations between \(\log f\) and other parameters, including intrinsic (de-beamed) peak frequency, \(\log \nu _{\mathrm{p}}^{\mathrm{in}}\), intrinsic polarization, \(\log P^{\mathrm{in}}\), and core-dominance parameter, \(\log R\), for the whole sample. In addition, we show that the ratio, f, can be estimated by R.     

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.     

Kelvin–Helmholtz Instability in a Cool Solar Jet in the Framework of Hall Magnetohydrodynamics: A Case Study

We investigate the conditions under which the magnetohydrodynamic (MHD) modes in a cylindrical magnetic flux tube moving along its axis become unstable against the Kelvin–Helmholtz (KH) instability. We use the dispersion relations of MHD modes obtained from the linearized Hall MHD equations for cool (zero beta) plasma by assuming real wave numbers and complex angular wave frequencies/complex wave phase velocities. The dispersion equations are solved numerically at fixed input parameters and varying values of the ratio \(l_{\mathrm{Hall}}/a\), where \(l_{\mathrm{Hall}} = c/\omega_{\mathrm{pi}}\) (\(c\) being the speed of light, and \(\omega_{\mathrm{pi}}\) the ion plasma frequency) and \(a\) is the flux tube radius. It is shown that the stability of the MHD modes depends upon four parameters: the density contrast between the flux tube and its environment, the ratio of external and internal magnetic fields, the ratio \(l_{\mathrm{Hall}}/a\), and the value of the Alfvén Mach number defined as the ratio of the tube axial velocity to Alfvén speed inside the flux tube. It is found that at high density contrasts, for small values of \(l_{\mathrm{Hall}}/a\), the kink (\(m = 1\)) mode can become unstable against KH instability at some critical Alfvén Mach number (or equivalently at critical flow speed), but a threshold \(l_{\mathrm{Hall}}/a\) can suppress the onset of the KH instability. At small density contrasts, however, the magnitude of \(l_{\mathrm{Hall}}/a\) does not affect noticeably the condition for instability occurrence – even though it can reduce the critical Alfvén Mach number. It is established that the sausage mode (\(m = 0\)) is not subject to the KH instability.     

Advective accretion flow properties around rotating black holes – application to GRO J1655-40

We examine the properties of the viscous dissipative accretion flow around rotating black holes in the presence of mass loss. Considering the thin disc approximation, we self-consistently calculate the inflow-outflow solutions and observe that the mass outflow rates decrease with the increase in viscosity parameter (\(\alpha \)). Further, we carry out the model calculation of quasi-periodic oscillation frequency (\(\nu _{\mathrm{QPO}}\)) that is frequently observed in black hole sources and observe that \(\nu ^\mathrm{max}_{\mathrm{QPO}}\) increases with the increase of black hole spin (\(a_k\)). Then, we employ our model in order to explain the High Frequency Quasi-Periodic Oscillations (HFQPOs) observed in black hole source GRO J1655-40. While doing this, we attempt to constrain the range of \(a_k\) based on observed HFQPOs (\(\sim \)300 Hz and \(\sim \)450 Hz) for the black hole source GRO J1655-40.     

Photospheric Shear Flows in Solar Active Regions and Their Relation to Flare Occurrence

Solar active regions (ARs) that produce major flares typically exhibit strong plasma shear flows around photospheric magnetic polarity inversion lines (MPILs). It is therefore important to quantitatively measure such photospheric shear flows in ARs for a better understanding of their relation to flare occurrence. Photospheric flow fields were determined by applying the Differential Affine Velocity Estimator for Vector Magnetograms (DAVE4VM) method to a large data set of 2548 coaligned pairs of AR vector magnetograms with 12-min separation over the period 2012?–?2016. From each AR flow-field map, three shear-flow parameters were derived corresponding to the mean (\(\langle S\rangle \)), maximum (\(S_{\mathrm{max}}\)) and integral (\(S_{\mathrm{sum}}\)) shear-flow speeds along strong-gradient, strong-field MPIL segments. We calculated flaring rates within 24 h as a function of each shear-flow parameter and we investigated the relation between the parameters and the waiting time (\(\tau \)) until the next major flare (class M1.0 or above) after the parameter observation. In general, it is found that the larger \(S_{\mathrm{sum}}\) an AR has, the more likely it is for the AR to produce flares within 24 h. It is also found that among ARs which produce major flares, if one has a larger value of \(S_{\mathrm{sum}}\) then \(\tau \) generally gets shorter. These results suggest that large ARs with widespread and/or strong shear flows along MPILs tend to not only be more flare productive, but also produce major flares within 24 h or less.     

Modulations of the surface magnetic field on the intra-cycle variability of total solar irradiance

Solar photospheric magnetic field plays a dominant role in the variability of total solar irradiance (TSI). The modulation of magnetic flux at six specific ranges on TSI is characterized for the first time. The daily flux values of magnetic field at four ranges are extracted from MDI/SOHO, together with daily flux of active regions (MF\(_{\text{ar}}\)) and quiet regions (MF\(_{\text{qr}}\)); the first four ranges (MF\(_{1\mbox{--}4}\)) are: 1.5–2.9, 2.9–32.0, 32.0–42.7, and 42.7–380.1 (\(\times 10^{18}\) Mx per element), respectively. Cross-correlograms show that MF₄, MF\(_{\text{qr}}\), and MF\(_{ \text{ar}}\) are positively correlated with TSI, while MF₂ is negatively correlated with TSI; the correlations between MF₁, MF₃ and TSI are insignificant. The bootstrapping tests confirm that the impact of MF₄ on TSI is more significant than that of MF\(_{\text{ar}}\) and MF\(_{\text{qr}}\), and MF\(_{\text{ar}}\) leads TSI by one rotational period. By extracting the rotational variations in the MFs and TSI, the modulations of the former on the latter at the solar rotational timescale are clearly illustrated and compared during solar maximum and minimum times, respectively. Comparison of the relative amplitudes of the long-term variation show that TSI is in good agreement with the variation of MF₄ and MF\(_{\text{ar}}\); besides, MF₂ is in antiphase with TSI, and it lags the latter by about 1.5 years.     

Addendum to: Strength of the Solar Coronal Magnetic Field – A Comparison of Independent Estimates Using Contemporaneous Radio and White-Light Observations

This addendum uses an alternate fit for the electron density distribution \(N(r)\) (see Figure 1) and estimates the coronal magnetic field using the new model. We find that the estimates of the magnetic field are in close agreement using both the models.

We have fit the \(N(r)\) distribution obtained from STEREO-A/COR1 and SOHO/LASCO-C2 using a fifth-order polynomial (see Figure 1). The expression can be written as

$$\begin{aligned} N_{\text{cor}}(r) &= 1.43 \times 10^{9} r^{-5} - 1.91 \times 10^{9} r^{-4} + 1.07 \times 10^{9} r^{-3} - 2.87 \times 10^{8} r^{-2} \\ &\quad {} + 3.76 \times 10^{7} r^{-1} - 1.91 \times 10^{6} , \end{aligned}$$

(1)

where \(N_{\text{cor}}(r)\) is in units of cm^?3 and \(r\) is in units of \(\mathrm{R}_{\odot}\). The background coronal electron density is enhanced by a factor of 5.5 at 2.63 \(\mathrm{R}_{\odot}\) during the coronal mass ejection (CME). The estimated coronal magnetic field strength (\(B\)) using radio data indicates that \(B(r) \approx(0.51\text{\,--\,}0.48) \pm 0.02\ \mathrm{G}\) in the range \(r \approx2.65\text{\, --\,}2.82\ \mathrm{R}_{\odot}\). The field strengths for STEREO-A/COR1 and SOHO/LASCO-C2 are ≈?0.32 G at \(r \approx 3.11\ \mathrm{R}_{\odot}\) and ≈?0.12 G at \(r \approx 4.40\ \mathrm{R}_{\odot}\), respectively.

     

A New Solar Imaging System for Observing High-Speed Eruptions: <Emphasis Type="Italic">Solar Dynamics Doppler Imager</Emphasis> (SDDI)

A new solar imaging system was installed at Hida Observatory to observe the dynamics of flares and filament eruptions. The system (Solar Dynamics Doppler Imager; SDDI) takes full-disk solar images with a field of view of \(2520~\mbox{arcsec} \times 2520~\mbox{arcsec}\) at multiple wavelengths around the \(\mathrm{H}\alpha\) line at 6562 Å. Regular operation was started in May 2016, in which images at 73 wavelength positions spanning from \(\mathrm{H}\alpha -9~\mathring{\mathrm{A}}\) to \(\mathrm{H}\alpha +9~\mathring{\mathrm{A}}\) are obtained every 15 seconds. The large dynamic range of the line-of-sight velocity measurements (\({\pm}\,400~\mbox{km}\,\mbox{s}^{-1}\)) allows us to determine the real motions of erupting filaments in 3D space. It is expected that SDDI provides unprecedented datasets to study the relation between the kinematics of filament eruptions and coronal mass ejections (CME), and to contribute to the real-time prediction of the occurrence of CMEs that cause a significant impact on the space environment of the Earth.     

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.     

Estimation of Reconnection Flux Using Post-eruption Arcades and Its Relevance to Magnetic Clouds at 1 AU

We report on a new method to compute the flare reconnection (RC) flux from post-eruption arcades (PEAs) and the underlying photospheric magnetic fields. In previous works, the RC flux has been computed using the cumulative flare ribbon area. Here we obtain the RC flux as the flux in half of the area underlying the PEA in EUV imaged after the flare maximum. We apply this method to a set of 21 eruptions that originated near the solar disk center in Solar Cycle 23. We find that the RC flux from the arcade method (\(\Phi_{\mathrm{rA}}\)) has excellent agreement with the flux from the flare-ribbon method (\(\Phi_{\mathrm{rR}}\)) according to \(\Phi_{\mathrm{rA}} = 1.24(\Phi_{\mathrm{rR}})^{0.99}\). We also find \(\Phi_{\mathrm{rA}}\) to be correlated with the poloidal flux (\(\Phi_{\mathrm{P}}\)) of the associated magnetic cloud at 1 AU: \(\Phi_{\mathrm{P}} = 1.20(\Phi_{\mathrm{rA}})^{0.85}\). This relation is nearly identical to that obtained by Qiu et al. (Astrophys. J. 659, 758, 2007) using a set of only 9 eruptions. Our result supports the idea that flare reconnection results in the formation of the flux rope and PEA as a common process.     

Improved Determination of the Location of the Temperature Maximum in the Corona

The most used method to calculate the coronal electron temperature [\(T_{\mathrm{e}} (r)\)] from a coronal density distribution [\(n_{\mathrm{e}} (r)\)] is the scale-height method (SHM). We introduce a novel method that is a generalization of a method introduced by Alfvén (Ark. Mat. Astron. Fys. 27, 1, 1941) to calculate \(T_{\mathrm{e}}(r)\) for a corona in hydrostatic equilibrium: the “HST” method. All of the methods discussed here require given electron-density distributions [\(n_{\mathrm{e}} (r)\)] which can be derived from white-light (WL) eclipse observations. The new “DYN” method determines the unique solution of \(T_{\mathrm{e}}(r)\) for which \(T_{\mathrm{e}}(r \rightarrow \infty) \rightarrow 0\) when the solar corona expands radially as realized in hydrodynamical solar-wind models. The applications of the SHM method and DYN method give comparable distributions for \(T_{\mathrm{e}}(r)\). Both have a maximum [\(T_{\max}\)] whose value ranges between 1?–?3 MK. However, the peak of temperature is located at a different altitude in both cases. Close to the Sun where the expansion velocity is subsonic (\(r < 1.3\,\mathrm{R}_{\odot}\)) the DYN method gives the same results as the HST method. The effects of the other free parameters on the DYN temperature distribution are presented in the last part of this study. Our DYN method is a new tool to evaluate the range of altitudes where the heating rate is maximum in the solar corona when the electron-density distribution is obtained from WL coronal observations.     

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.     

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).     

The Effect of Magnetic and Density Differences on the Fast Kink Oscillations of Neighboring Coronal Loops

It is reasonable that neighboring coronal loops may obtain similar momentum during a flare. The fast kink oscillations (FKOs) between them are thus mainly influenced by their physical differences. We discuss the dependencies of FKO on the physical properties of coronal loops in a low-\(\beta \) thin-tube approximation. From the analysis, we obtain the analytic relationship between the density [\(\rho _{\mathrm{i}}\)] and magnetic field [\(B\)] of loops and the corresponding period [\(\tau \)] and amplitude [\(A\)] of FKO, which may provide us with a powerful tool to diagnose the physical differences between neighboring loops.     

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.     

Dust color temperature distribution of two FIR cavities at IRIS and AKARI maps

By systematically searching the region of far infrared loops, we found a number of huge cavity-like dust structures at \(60\,\mu \hbox {m}\) and \(100\,\mu \hbox {m}\) IRIS maps. By checking these with AKARI maps (\(90\,\mu \hbox {m}\) and \(140\,\mu \hbox {m}\)), two new cavity-like structures (sizes \(\sim \) \( 2.7\,\hbox {pc} \times 0.8\,\hbox {pc}\) and \(\sim \) \( 1.8\,\hbox {pc} \times 1\,\hbox {pc}\)) located at R.A. (\(\hbox {J}2000)=14^{h}41^{m}23^{s}\) and Dec. \((\hbox {J}2000)=-64^{\circ }04^{\prime }17^{{\prime }{\prime }}\) and R.A. \((\hbox {J}2000)=05^{h}05^{m}35^{s}\) and Dec. \((\hbox {J}2000)=-\,69^{\circ }35^{\prime } 25^{{\prime }{\prime }}\) were selected for the study. The difference in the average dust color temperatures calculated using IRIS and AKARI maps of the cavity candidates were found to be \(3.2\pm 0.9\,\hbox {K}\) and \(4.1\pm 1.2\,\hbox {K}\), respectively. Interestingly, the longer wavelength AKARI map gives larger values of dust color temperature than that of the shorter wavelength IRIS maps. Possible explanation of the results will be presented.