We present analysis results of the energy spectra of MCG-2-58-22 associated with occasional flares which appear in a long-term X-ray light curve. We measure an intrinsic power-law slope of this object to be Γ =1.74 ± 0.02 in the energy range of ~ 1 -5 keV and find that this slope is little affected by flares. We confirm that there exists a broad excess emission above 5 keV to the power-law continuum. The excess emission is less variable compared with a flux variation of flare and tends to be relatively weak during flares. A soft X-ray spectrum is also found to change, implying the presence of a variable soft component. We discuss the implications of these spectral variations.

The basic objective of helioseismology is to determine the structure and the dynamics of the Sun by analysing the frequency spectrum of the solar oscillations. Accurate frequency measurements provide information that enables us to probe the solar interior structure and the dynamics. Therefore the frequency of the solar oscillation is the most fundamental and important information to be extracted from the solar oscillation observation. This is why many efforts have been put into the development of accurate data analysis techniques, as well as observational efforts. To test one's data analysis method, a realistic artificial data set is essential because the newly suggested method is calibrated with a set of artificial data with predetermined parameters. Therefore, unless test data sets reflect the real solar oscillation data correctly, such a calibration is likely incomplete and a unwanted systematic bias may result in. Unfortunately, however, commonly used artificial data generation algorithms insufficiently accommodate physical properties of the stochastic excitation mechanism. One of reason for this is that it is computaionally very expensive to solve the governing equation directly. In this paper we discuss the nature of solar oscillation excitation and suggest an efficient algorithm to generate the artificial solar oscillation data. We also briefly discuss how the results of this work can be applied in the future studies.

Utilizing a new version of the sunspot number and group sunspot number dataset available since 2015, we have statistically studied the relationship between solar activity parameters describing solar cycles and the slope of the linear relationship between the monthly sunspot numbers and the monthly number of active days in percentage (AD). As an effort of evaluating possibilities in use of the number of active days to predict solar activity, it is worthwhile to revisit and extend the analysis performed earlier. In calculating the Pearson’s linear correlation coefficient r, the Spearman’s rank-order correlation coefficient rs, and the Kendall’s τ coefficient with the rejection probability, we have calculated the slope for a given solar cycle in three different ways, namely, by counting the spotless day that occurred during the ascending phase and the descending phase of the solar cycle separately, and during the period corresponding to solar minimum ± 2 years as well. We have found that the maximum solar sunspot number of a given solar cycle and the duration of the ascending phase are hardly correlated with the slope of a linear function of the monthly sunspot numbers and AD. On the other hand, the duration of a solar cycle is found to be marginally correlated with the slope with the rejection probabilities less than a couple of percent. We have also attempted to compare the relation of the monthly sunspot numbers with AD for the even and odd solar cycles. It is inconclusive, however, that the slopes of the linear relationship between the monthly group numbers and AD are subject to the even and odd solar cycles.

We explore the associations between the total sunspot area, solar north-south asymmetry, and Southern Oscillation Index and the physical characteristics of clouds by calculating normalized cross-correlations, motivated by the idea that the galactic cosmic ray influx modulated by solar activity may cause changes in cloud coverage, and in turn the Earth’s climate. Unlike previous studies based on the relative difference, we have employed cloud data as a whole time-series without detrending. We found that the coverage of high-level and low-level cloud is at a maximum when the solar north-south asymmetry is close to the minimum, and one or two years after the solar north-south asymmetry is at a maximum, respectively. The global surface air temperature is at a maximum five years after the solar north-south asymmetry is at a maximum, and the optical depth is at a minimum when the solar north-south asymmetry is at a maximum. We also found that during the descending period of solar activity, the coverage of low-level cloud is at a maximum, and global surface air temperature and cloud optical depth are at a minimum, and that the total column water vapor is at a maximum one or two years after the solar maximum.

In this study, we investigate the associations between the solar variability and teleconnection indices, which influence atmospheric circulation and subsequently, the spatial distribution of the global pressure system. A study of the link between the Sun and a large-scale mode of climate variability, which may indirectly affect the Earth’s climate and weather, is crucial because the feedbacks of solar variability to an autogenic or internal process should be considered with due care. We have calculated the normalized cross-correlations of the total sunspot area, the total sunspot number, and the solar North–South asymmetry with teleconnection indices. We have found that the Southern Oscillation Index (SOI) index is anti-correlated with both solar activity and the solar North–South asymmetry, with a ∼3-year lag. This finding not only agrees with the fact that El Niño episodes are likely to occur around the solar maximum, but also explains why tropical cyclones occurring in the solar maximum periods and in El Niño periods appear similar. Conversely, other teleconnection indices, such as the Arctic Oscillation (AO) index, the Antarctic Oscillation (AAO) index, and the Pacific-North American (PNA) index, are weakly or only slightly correlated with solar activity, which emphasizes that response of terrestrial climate and weather to solar variability are local in space. It is also found that correlations between teleconnection indices and solar activity are as good as correlations resulting from the teleconnection indices themselves.

Understanding solar influences on extreme weather is important. Insight into the causes of extreme weather events, including the solar-terrestrial connection, would allow better preparation for these events and help minimize the damage caused by disasters that threaten the human population. In this study, we examined category three, four, and five tropical cyclones that occurred in the western North Pacific Ocean from 1977 to 2016. We compared long-term trends in the positions of tropical cyclone occurrence and development with variations of the observed sunspot area, the solar North-South asymmetry, and the southern oscillation index (SOI). We found that tropical cyclones formed, had their maximum intensity, and terminated more northward in latitude and more westward in longitude over the period analyzed; they also became stronger during that period. It was found that tropical cyclones cannot be correlated or anti-correlated with the solar cycle. No evidence showing that properties (including positions of occurrence/development and other characteristics) of tropical cyclones are modulated by solar activity was found, at least not in terms of a spectral analysis using the wavelet transform method.

The solar magnetic field plays a central role in the field of solar research, both theoretically and practically. Sunspots are an important observational constraint since they are considered a discernable tracer of emerged magnetic flux tubes, providing the longest running records of solar magnetic activity. In this presentation, we first review the statistical properties of the latitudinal distribution of sunspots and discuss their implications. The phase difference between paired wings of the butterfly diagram has been revealed. Sunspots seem to emerge with the exponential distribution on top of slowly varying trends by periods of ~11 years, which is considered multiplicative rather than additive. We also present a concept for the center-oflatitude (COL) and its use. With this, one may sort out a traditional butterfly diagram and find new features. It is found that the centroid of the COL does not migrate monotonically toward the equator, appearing to form an ‘active latitude’. Furthermore, distributions of the COL as a function of latitude depend on solar activity and the solar North-South asymmetry. We believe that these findings serve as crucial diagnostic tools for any potential model of the solar dynamo. Finally, we find that as the Sun modulates the amount of observed galactic cosmic ray influx, the solar North-South asymmetry seems to contribute to the relationship between the solar variability and terrestrial climate change.

Solar activity is known to be linked to changes in the Earth’s weather and climate. Nonetheless, for other types of extreme weather, such as tropical cyclones (TCs), the available evidence is less conclusive. In this study the modulation of TC genesis over the western North Pacific by the solar activity is investigated, in comparison with a large-scale environmental parameter, i.e., El-Niño-Southern Oscillation (ENSO). For this purpose, we have obtained the best track data for TCs in the western North Pacific from 1977 to 2016, spanning from the solar cycle 21 to the solar cycle 24. We have confirmed that in the El-Niño periods TCs tend to form in the southeast, reach its maximum strength in the southeast, and end its life as TSs in the northeast, compared with the La-Niña periods. TCs occurring in the El-Niño periods are found to last longer compared with the La-Niña periods. Furthermore, TCs occurring in the El-Niño periods have a lower central pressure at their maximum strength than those occurring in the La-Niña periods. We have found that TCs occurring in the solar maximum periods resemble those in the El-Niño periods in their properties. We have also found that TCs occurring in the solar descending periods somehow resemble those in the El-Niño periods in their properties. To make sure that it is not due to the ENSO effect, we have excluded TCs both in the El-Niño periods and in the La-Niña periods from the data set and repeated the analysis. In addition to this test, we have also reiterated our analysis twice with TCs whose maximum sustained winds speed exceeds 17 m/s, instead of 33 m/s, as well as TCs designated as a typhoon, which ends up with the same conclusions.

An analysis of light curves and spectra of observed gamma-ray bursts in gamma-ray ranges is frequently demanded because the prompt emission contains immediate details regarding the central engine of gamma-ray bursts (GRBs). We have revisited the relationship between the collimation-corrected peak luminosity and the spectral lag, investigating the lag-luminosity relationships in great detail by focusing on spectral lags resulting from all possible combinations of channels. Firstly, we compiled the opening angle data and demonstrated that the distribution of opening angles of 205 long GRBs is represented by a double Gaussian function having maxima at ~ 0.1 and ~ 0.3 radians. We confirmed that the peak luminosity and the spectral lag are anti-correlated, both in the observer frame and in the source frame. We found that, in agreement with our previous conclusion, the correlation coefficient improves significantly in the source frame. It should be noted that spectral lags involving channel 2 (25-50 keV) yield high correlation coefficients, where Swift/Burst Alert Telescope (BAT) has four energy channels (channel 1: 15-25 keV, channel 2: 25-50 keV, channel 3: 50-100 keV, channel 4: 100-200 keV). We also found that peak luminosity is positively correlated with peak energy.

We are motivated by both the accumulating evidence for the connection of solar variability to the chemistry of nitrogen oxide in the atmosphere and recent finding that the Galactic cosmic-ray (GCR) influx is associated with the solar northsouth asymmetry. We have analyzed the measured pH in precipitation over the 109 stations distributed in the United States. We have found that data of pH in precipitation as a whole appear to be marginally anti-correlated with the solar asymmetry. That is, rain seems to become less acidic when the southern hemisphere of the Sun is more active. The acidity of rain is also found to be correlated with the atmospheric temperature, while not to be correlated with solar activity itself. We have carried on the analysis with two subsamples in which stations located in the east and in the west. We find that the pH data derived from the eastern stations which are possibly polluted by sulfur oxides and nitrogen oxides are not correlated with the solar asymmetry, but with the temperature. On the contrary, the pH data obtained from the western stations are found to be marginally anti-correlated with the solar asymmetry. In addition, the pH data obtained from the western stations are found to be correlated with the solar UV radiation. We conclude by briefly pointing out that a role of the solar asymmetry in the process of acidification of rain is to be further examined particularly when the level of pollution by sulfur oxides and nitrogen oxides is low.

Solar variability is widely known to affect the interplanetary space and in turn the Earth’s electromagnetical environment on the basis of common periodicities in the solar and geomagnetic activity indices. The goal of this study is twofold. Firstly, we attempt to associate modes by comparing a temporal behavior of the power of geomagnetic activity parameters since it is barely sufficient searching for common peaks with a similar periodicity in order to causally correlate geomagnetic activity parameters. As a result of the wavelet transform analysis we are able to obtain information on the temporal behavior of the power in the velocity of the solar wind, the number density of protons in the solar wind, the AE index, the Dst index, the interplanetary magnetic field, B and its three components of the GSM coordinate system, BX, BY, BZ. Secondly, we also attempt to search for any signatures of influence on the space environment near the Earth by inner planets orbiting around the Sun. Our main findings are as follows: (1) Parameters we have investigated show periodicities of ~ 27 days, ~ 13.5 days, ~ 9 days. (2) The peaks in the power spectrum of BZ appear to be split due to an unknown agent. (3) For some modes powers are not present all the time and intervals showing high powers do not always coincide. (4) Noticeable peaks do not emerge at those frequencies corresponding to the synodic and/or sidereal periods of Mercury and Venus, which leads us to conclude that the Earth’s space environment is not subject to the shadow of the inner planets as suggested earlier.

As the prediction of geomagnetic storms is becoming an important and practical problem, conditions in the Earth’s magnetosphere have been studied rigorously in terms of those in the interplanetary space. Another approach to space weather forecast is to deal with it as a probabilistic geomagnetic storm forecasting problem. In this study, we carry out detailed statistical analysis of solar wind parameters and geomagnetic indices examining the dependence of the distribution on the solar cycle and annual variations. Our main findings are as follows: (1) The distribution of parameters obtained via the superimposed epoch method follows the Gaussian distribution. (2) When solar activity is at its maximum the mean value of the distribution is shifted to the direction indicating the intense environment. Furthermore, the width of the distribution becomes wider at its maximum than at its minimum so that more extreme case can be expected. (3) The distribution of some certain heliospheric parameters is less sensitive to the phase of the solar cycle and annual variations. (4) The distribution of the eastward component of the interplanetary electric field BV and the solar wind driving function BV2, however, appears to be all dependent on the solar maximum/minimum, the descending/ascending phases of the solar cycle and the equinoxes/solstices. (5) The distribution of the AE index and the Dst index shares statistical features closely with BV and BV2 compared with other heliospheric parameters. In this sense, BV and BV2 are more robust proxies of the geomagnetic storm. We conclude by pointing out that our results allow us to step forward in providing the occurrence probability of geomagnetic storms for space weather and physical modeling.

Parameters associated with solar minimum have been studied to relate them to solar activity at solar maximum so that one could possibly predict behaviors of an upcoming solar cycle. The number of active days has been known as a reliable indicator of solar activity around solar minimum. Active days are days with sunspots reported on the solar disk. In this work, we have explored the relationship between the sunspot numbers at solar maximum and the characteristics of the monthly number of active days. Specifically, we have statistically examined how the maximum monthly sunspot number of a given solar cycle is correlated with the slope of the linear relationship between monthly sunspot numbers and the monthly number of active days for the corresponding solar cycle. We have calculated the linear correlation coefficient r and the Spearman rank-order correlation coefficient rs for data sets prepared under various conditions. Even though marginal correlations are found, they turn out to be insufficiently significant (r ~ 0.3). Nonetheless, we have confirmed that the slope of the linear relationship between monthly sunspot numbers and the monthly number of active days is less steep when solar cycles belonging to the "Modern Maximum" are considered compared with rests of solar cycles. We conclude, therefore, that the slope of the linear relationship between monthly sunspot numbers and the monthly number of active days is indeed dependent on the solar activity at its maxima, but that this simple relationship should be insufficient as a valid method to predict the following solar activity amplitude.

We revisit the relation between the peak luminosity Liso and the spectral time lag in the source frame. Since gamma-ray bursts (GRBs) are generally thought to be beamed, it is natural to expect that the collimation-corrected peak luminosity may well correlate with the spectral time lag in the source frame if the lag-luminosity relation in the GRB source frame exists. With 12 long GRBs detected by the Swift satellite, whose redshift and spectral lags in the source frame are known, we computed L0,H and L0,W using bulk Lorentz factors Γ0,H and Γ0,W archived in the published literature, where the subscripts H and W represent homogeneous and wind-like circumburst environments, respectively. We have confirmed that the isotropic peak luminosity correlates with the spectral time lag in the source frame. We have also confirmed that there is an anti-correlation between the source-frame spectral lag and the peak energy, Epeak (1 + z) in the source frame. We have found that the collimation-corrected luminosity correlates in a similar way with the spectral lag, except that the correlations are somewhat less tight. The correlation in the wind density profile seems to agree with the isotropic peak luminosity case better than in the homogeneous case. Finally we conclude by briefly discussing its implications.

Monitoring sunspots consistently is the most basic step required to study various aspects of solar activity. To achieve this goal, the observers must regularly calculate their own correction factor k and keep it stable. Relatively recently, two observing teams in South Korea have presented interesting papers which claim that revisions that take the yearly-basis k into account lead to a better agreement with the international relative sunspot number Ri, and that yearly k apparently varies with the solar cycle. In this paper, using artificial data sets we have modeled the sunspot numbers as a superposition of random noise and a slowly varying background function, and attempted to investigate whether the variation in the correction factor is coupled with the solar cycle. Regardless of the statistical distributions of the random noise, we have found the correction factor increases as sunspot numbers increase, as claimed in the reports mentioned above. The degree of dependence of correction factor k on the sunspot number is subject to the signal-to-noise ratio. Therefore, we conclude that apparent dependence of the value of the correction factor k on the phase of the solar cycle is not due to a physical property, but a statistical property of the data.