• Journal of Positioning, Navigation, and Timing
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• v.5 no.2
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• pp.87-96
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• 2016

The ionospheric error, which is one of many error elements considered during the Global Navigation Satellite System (GNSS) positioning, is hard to be predicted due to the influence of geomagnetic activity and irregular solar activities. Thus, the present study analyzed a change pattern in the ionosphere through Global Ionosphere Map (GIM) data for 12 years from 2003 to 2014 and a variation in the Slant Total Electron Content (STEC) between Sinuiju and Busan which was the longest range in the southeastern direction of the Korean Peninsula. The variation in the STEC verified the diurnal, annual, and solar cycle variations due to the influence of solar activity. The diurnal variation was characterized that the variation in the STEC started to increase from 6-7 am and reached the maximum at 13-14 pm followed by being decreased. The seasonal variation was characterized that the variation in the STEC was high in spring and autumn whereas it was low in summer and winter. The solar cycle variation revealed that the variation in the STEC increased during solar maximum and decreased during solar minimum. The variation in the STEC was up to 20 Total Electron Content Unit (TECU) during the solar minimum and up to 60 TECU during solar maximum.

• Journal of Astronomy and Space Sciences
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• v.23 no.3
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• pp.227-236
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• 2006

The fractal dimension is a quantitative parameter describing the characteristics of irregular time series. In this study, we use this parameter to analyze the irregular aspects of solar activity and to predict the maximum sunspot number in the following solar cycle by examining time series of the sunspot number. For this, we considered the daily sunspot number since 1850 from SIDC (Solar Influences Data analysis Center) and then estimated cycle variation of the fractal dimension by using Higuchi's method. We examined the relationship between this fractal dimension and the maximum monthly sunspot number in each solar cycle. As a result, we found that there is a strong inverse relationship between the fractal dimension and the maximum monthly sunspot number. By using this relation we predicted the maximum sunspot number in the solar cycle from the fractal dimension of the sunspot numbers during the solar activity increasing phase. The successful prediction is proven by a good correlation (r=0.89) between the observed and predicted maximum sunspot numbers in the solar cycles.

• The Bulletin of The Korean Astronomical Society
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• v.41 no.2
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• pp.67.1-67.1
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• 2016

We examined the relations between CME speed and properties of magnetic helicity in the source region such as helicity injection rate and total unsigned magnetic flux, which reflect the magnetic energy in the active region. For this, we selected 22 CMEs occurred during the increasing phase of solar cycle 24, which shows extremely low activities and classified them into two groups according to evolution pattern of helicity injection rate. We then compared the relations with those from previous study based on the events in solar cycle 23. As the results, we found several properties as follows: (1) Both of CME speed and helicity parameters have very small values since we only considered increasing phase; (2) among 22 CMEs, only 6 events (27%) are classified as group B, which show sign reversal of helicity injection and they follow behind of appearance of group A events. This fact is well coincide with the trend of solar cycle 23 that only group A events was observed in the first 3 years of the period; (3) as the solar activity is increasing, the CME speed and helicity parameters are also increasing. Based on the observations of solar cycle 23, the helicity parameters was still increasing in spite of decreasing solar activity after maximum period.

• Journal of The Korean Astronomical Society
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• v.50 no.2
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• pp.21-27
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• 2017

The autoregressive method provides a univariate procedure to predict the future sunspot number (SSN) based on past record. The strength of this method lies in the possibility that from past data it yields the SSN in the future as a function of time. On the other hand, its major limitation comes from the intrinsic complexity of solar magnetic activity that may deviate from the linear stationary process assumption that is the basis of the autoregressive model. By analyzing the residual errors produced by the method, we have obtained the following conclusions: (1) the optimal duration of the past time for the forecast is found to be 8.5 years; (2) the standard error increases with prediction horizon and the errors are mostly systematic ones resulting from the incompleteness of the autoregressive model; (3) there is a tendency that the predicted value is underestimated in the activity rising phase, while it is overestimated in the declining phase; (5) the model prediction of a new Solar Cycle is fairly good when it is similar to the previous one, but is bad when the new cycle is much different from the previous one; (6) a reasonably good prediction of a new cycle can be made using the AR model 1.5 years after the start of the cycle. In addition, we predict the next cycle (Solar Cycle 25) will reach the peak in 2024 at the activity level similar to the current cycle.

• 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.40 no.2
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• pp.45-57
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• 2023

This study examined the effect of solar flux (F10.7) and sunspots number (R) on the daily variation of equatorial electrojet (EEJ) and morning/afternoon counter electrojet (MCEJ/ACEJ) in the ionospheric E region across the eight longitudinal sectors during quiet days from January 2008 to December 2013. In particular, we focus on both minimum and maximum solar cycle of 24. For this purpose, we have collected a 6-year ground-based magnetic data from multiple stations to investigate EEJ/CEJ climatology in the Peruvian, Brazilian, West & East African, Indian, Southeast Asian, Philippine, and Pacific sectors with the corresponding F10.7 and R data from satellites simultaneously. Our results reveal that the variations of monthly mean EEJ intensities were consistent with the variations of solar flux and sunspot number patterns of a cycle, further indicating that there is a significant seasonal and longitudinal dependence. During the high solar cycle period, F10.7 and R have shown a strong peak around equinoctial months, consequently, the strong daytime EEJs occurred in the Peruvian and Southeast Asian sectors followed by the Philippine regions throughout the years investigated. In those sectors, the correlation between the day Maxima EEJ and F10.7 strengths have a positive value during periods of high solar activity, and they have relatively higher values than the other sectors. A predominance of MCEJ occurrences is observed in the Brazilian (TTB), East African (AAE), and Peruvian (HUA) sectors. We have also observed the CEJ dependence on solar flux with an anti-correlation between ACEJ events and F10.7 are observed especially during a high solar cycle period.

• Journal of Astronomy and Space Sciences
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• v.36 no.3
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• pp.159-168
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• 2019

In solstices during the solar minimum, the hemispheric difference of the equatorial ionization anomaly (EIA) intensity (hereafter hemispheric asymmetry) is understood as being opposite in the morning and afternoon. This phenomenon is explained by the temporal variation of the combined effects of the fountain process and interhemispheric wind. However, the mechanism applied to the observations during the solar minimum has not yet been validated with observations made during other periods of the solar cycle. We investigate the variability of the hemispheric asymmetry with local time (LT), altitude, season, and solar cycle using the electron density taken by the CHAllenging Minisatellite Payload satellite and the global total electron content (TEC) maps acquired during 2001-2008. The electron density profiles provided by the Constellation Observing System for Meteorology, Ionosphere, and Climate satellites during 2007-2008 are also used to investigate the variation of the hemispheric asymmetry with altitude during the solar minimum. During the solar minimum, the location of a stronger EIA moves from the winter hemisphere to the summer hemisphere around 1200-1400 LT. The reversal of the hemispheric asymmetry is more clearly visible in the F-peak density than in TEC or in topside plasma density. During the solar maximum, the EIA in the winter hemisphere is stronger than that in the summer hemisphere in both the morning and afternoon. When the location of a stronger EIA in the afternoon is viewed as a function of the year, the transition from the winter hemisphere to the summer hemisphere occurs near 2004 (yearly average F10.7 index = 106). We discuss the mechanisms that cause the variation of the hemispheric asymmetry with LT and solar cycle.

• Journal of Astronomy and Space Sciences
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• v.29 no.2
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• pp.103-113
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• 2012

The ButterStar Observatory at the Dongducheon High School has been working for photographic observations of the Sun since October 16, 2002. In this study, we observed the Sun at the ButterStar observatory for 3,364 days from October 16, 2002 to December 31, 2011, and analyzed the photographic sunspot data obtained in 1,965 days. The correction factor $K_b$ for the entire observing period is 0.9519, which is calculated using the linear least square method to the relationship between the daily sunspot number, $R_B$, and the daily international relative sunspot number, $R_i$. The yearly correction factor calculated for each year varies slightly from year to year and shows a trend to change along the solar cycle. The correction factor is larger during the solar maxima and smaller during the solar minima in general. This implies that the discrepancy between a relative sunspot number, R, and the daily international relative sunspot number, $R_i$, can be reduced by using a yearly correction factor. From 2002 to 2008 in solar cycle 23, 35.4% and 64.6% of sunspot groups and 35.1% and 64.9% of isolated sunspots in average occurred in the northern hemisphere and in the southern hemisphere, respectively, and from 2008 to 2011 in solar cycle 24, 61.3% and 38.7% of sunspot groups and 65.0% and 35.0% of isolated sunspots were observed, respectively. This result shows that the occurrence frequency for each type of sunspot group changes along the solar cycle development, which can be interpreted as the emerging and decaying process of sunspot groups is different depending on the phase of solar cycle. Therefore, it is considered that a following study would contribute to the efforts to understand the dependence of the dynamo mechanism on the phase of solar cycle.

• Publications of The Korean Astronomical Society
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• v.14 no.2
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• pp.103-112
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• 1999

We have investigated the solar activity variation with period shorter than 1000 days, through Fourier transformation of solar cycle 21 and 22 data. And real time predictions of the flare maximum intensity have been made by multilinear regression method to allow the use of multivariate vectors of sunspot groups or active region characteristics. In addition, we have examined the evolution of magnetic field and current density in active regions at times before and after flare occurrence, to check short term variability of solar activity. According to our results of calculation, solar activity changes with periods of 27.1, 28.0, 52.1, 156.3, 333.3 days for solar cycle 21 and of 26.5, 27.1, 28.9, 54.1, 154, 176.7, 384.6 days for solar cycle 22. Periodic components of about 27, 28, 53, 155 days are found simultaneously at all of two solar cycles. Finally, from our intensive analysis of solar activity data for three different terms of $1977\~1982,\; 1975\~1998,\;and\;1978\~1982$, we find out that our predictions coincide with observations at hit rate of $76\%,\;63\%$, 59 respectively.

• Journal of the Korean Solar Energy Society
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• v.37 no.5
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• pp.27-37
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• 2017

In this study, an artificial solar simulator composed of a 2.5 kW Xe-Arc lamp and mirror reflector was used to carry out the solar thermal two step thermochemical water decomposition cycle which can produce high efficiency continuous hydrogen production. Through various operating conditions, the change of hydrogen production due to the possibility of a dual-zone reactor and heat recovery were experimentally analyzed. Based on the reaction temperature of Thermal-Reduction step and Water-Decomposition step at $1,400^{\circ}C$ and $1,000^{\circ}C$ respectively, the hydrogen production decreased by 23.2% under the power off condition, and as a result of experiments using heat recovery technology, the hydrogen production increased by 33.8%. Therefore, when a thermochemical two-step water decomposition cycle is conducted using a dual-zone reactor with heat recovery, it is expected that the cycle can be operated twice over a certain period of time and the hydrogen production amount is increased by at least 53.5% compared to a single reactor.