• Journal of Astronomy and Space Sciences
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• v.35 no.2
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• pp.55-66
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• 2018

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-of-latitude (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.

• Journal of Astronomy and Space Sciences
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• v.36 no.4
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• pp.225-234
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• 2019

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.

• Journal of Astronomy and Space Sciences
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• v.28 no.2
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• pp.103-108
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• 2011

The latitudinal variation of sunspots appearing during the period from 1874 to 2009 has been studied in terms of centerof-latitude (COL). The butterfly diagram has been used to study the evolution of the magnetic field and the dynamics at the bottom of the solar convection zone. Short-term periodicities have been of particular interest, in that they are somehow related to the structure and dynamics of the solar interior. We thus have focused our investigation on shortterm periodicities. We first calculated COL by averaging the latitude of sunspots with the weight function in area. Then, we analyzed the time series of COL using the wavelet transform technique. We found that a periodicity of ~5 years is the most dominant feature in the time series of COL, with the exception of the ~11 year solar cycle itself. This periodicity can be easily understood by considering small humps between the minima in the area-weighted butterfly diagram. However, we find that periodicities of ~1.3 (0.064), ~1.5 (0.056), or ~1.8 (0.046) years ($\frac{1}{month}$), month ), which have been previously suggested as evidence of links between the changing structure of the sunspot zone and the tachocline rotation rate oscillations, are insignificant and inconsistent. We therefore conclude that the only existing short-term periodicity is of ~5 years, and that periodicities of ~1.3, ~1.5, or ~1.8 years are likely to be artifacts due to random noise of small sunspots.

• Journal of Astronomy and Space Sciences
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• v.30 no.3
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• pp.163-168
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• 2013

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 $r_s$ 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.

• Journal of Astronomy and Space Sciences
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• v.28 no.4
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• pp.261-265
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• 2011

We investigate the sunspot area data spanning from solar cycles 1 (March 1755) to 23 (December 2010) in time domain. For this purpose, we employ the Hilbert transform analysis method, which is used in the field of information theory. One of the most important advantages of this method is that it enables the simultaneous study of associations between the amplitude and the phase in various timescales. In this pilot study, we adopt the alternating sunspot area as a function of time, known as Bracewell transformation. We first calculate the instantaneous amplitude and the instantaneous phase. As a result, we confirm a ~22-year periodic behavior in the instantaneous amplitude. We also find that a behavior of the instantaneous amplitude with longer periodicities than the ~22-year periodicity can also be seen, though it is not as straightforward as the obvious ~22-year periodic behavior revealed by the method currently proposed. In addition to these, we note that the phase difference apparently correlates with the instantaneous amplitude. On the other hand, however, we cannot see any obvious association of the instantaneous frequency and the instantaneous amplitude. We conclude by briefly discussing the current status of development of an algorithm for the solar activity forecast based on the method presented, as this work is a part of that larger project.

• Journal of Astronomy and Space Sciences
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• v.29 no.2
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• pp.97-101
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• 2012

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 $R_i$, 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.

• Journal of Astronomy and Space Sciences
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• v.29 no.3
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• pp.253-258
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• 2012

We revisit the relation between the peak luminosity $L_{iso}$ 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 $L_{0,H}$ and $L_{0,W}$ using bulk Lorentz factors ${\Gamma}_{0,H}$ and ${\Gamma}_{0,W}$ 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, $E_{peak}$ (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.

• Journal of Astronomy and Space Sciences
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• v.26 no.3
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• pp.287-294
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• 2009

In helioseismology it is normally assumed that p-mode oscillations are excited in a statistically independent fashion. Unfortunately, however, this issue is not clearly settled down in that two experiments exist, which apparently look in discrepancy. That is, Appourchaux et al. (2000) looked at bin-to-bin correlation and found no evidence that the assumption is invalid. On the other hand, Roth (2001) reported that p-mode pairs with nearby frequencies tend to be anti-correlated, possibly by a mode-coupling effect. This work is motivated by an idea that one may test if there exists an excess of anticorrelated power variations of pairs of solar p-modes. We have analyzed a 72-day MDI spherical-harmonic time series to examine temporal variations of p-mode power and their correlation. The power variation is computed by a running-window method after the previous study by Roth (2001), and then distribution function of power correlation between mode pairs is produced. We have confirmed Roth's result that there is an excess of anti-correlated p-mode pairs with nearby frequencies. On the other hand, the amount of excess was somewhat smaller than the previous study. Moreover, the distribution function does not exhibit significant change when we paired modes with non-nearby frequencies, implying that the excess is not due to mode coupling. We conclude that the origin of this excess of anticorrelations may not be a solar physical process, by pointing out the possibility of statistical bias playing the central role in producing the excess.

• Journal of Astronomy and Space Sciences
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• v.37 no.1
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• pp.43-50
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• 2020

We have developed an algorithm for tracking coronal mass ejection (CME) propagation that allows us to estimate CME speed and its arrival time at Earth. The algorithm may be used either to forecast the CME's arrival on the day of the forecast or to update the CME tracking information for the next day's forecast. In our case study, we successfully tracked CME propagation using the algorithm based on g-values of interplanetary scintillation (IPS) observation provided by the Institute for Space-Earth Environmental Research (ISEE). We were able to forecast the arrival time (Δt = 0.30 h) and speed (Δv = 20 km/s) of a CME event on October 2, 2000. From the CME-interplanetary CME (ICME) pairs provided by Cane & Richardson (2003), we selected 50 events to evaluate the algorithm's forecast capability. Average errors for arrival time and speed were 11.14 h and 310 km/s, respectively. Results demonstrated that g-values obtained continuously from any single station observation were able to be used as a proxy for CME speed. Therefore, our algorithm may give stable daily forecasts of CME position and speed during propagation in the region of 0.2-1 AU using the IPS g-values, even if IPS velocity observations are insufficient. We expect that this algorithm may be widely accepted for use in space weather forecasting in the near future.

• Journal of Astronomy and Space Sciences
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• v.23 no.3
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• pp.199-208
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• 2006

The terrestrial impact cratering record recently has been examined in the time domain by Chang & Moon (2005). It was found that the ${\sim}26$ Myr periodicity in the impact cratering rate exists over the last ${\sim}250$ Myrs. Such a periodicity can be found regardless of the lower limit of the diameter up to D ${\sim}35km$. It immediately called pros and cons. The aim of this paper is two-fold: (1) to test if reported periodicities can be obtained with an independent method, (2) to see, as attempted earlier, if the phase is modulated. To achieve these goals we employ the time/frequency analysis and for the first time apply this method to the terrestrial impact cratering records. We have confirmed that without exceptions noticeable peaks appear around ${\sim}25$ Myr, corresponding to a frequency of ${\sim}0.04(Myr)^{-1}$. We also find periodicities in the data base including small impact craters, which are longer. Though the time/frequency analysis allows us to observe directly phase variations, we cannot find any indications of such changes. Instead, modes display slow variations of power in time. The time/frequency analysis shows a nonstationary behavior of the modes. The power can grow from just above the noise level and then decrease back to its initial level in a time of order of 10 Myrs.