• Journal of Astronomy and Space Sciences
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• v.32 no.4
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• pp.427-434
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• 2015

Coronal Mass Ejections (CME), which originate from active regions of the Sun's surface, e.g., sunspots, result in geomagnetic storms on Earth. The variation of the Earth's geomagnetic field during such storms induces surface currents that could cause breakdowns in electricity power grids. Hence, it is essential to both monitor Geomagnetically Induced Currents (GICs) in real time and analyze previous GIC data. In 2012, in order to monitor the variation of GICs, the Korean Space Weather Center (KSWC) installed an induced current measurement system at SINGAPYEONG Substation, which is equipped with 765 kV extra-high-voltage transformers. Furthermore, in 2014, two induced current measurement systems were installed on the 345 kV high-voltage transformers at the MIGEUM and SINPOCHEON substations. This paper reports the installation process of the induced current measurement systems at these three substations. Furthermore, it presents the results of both an analysis performed using GIC data measured at the SINGAPYEONG Substation during periods of geomagnetic storms from July 2013 through April 2015 and the comparison between the obtained GIC data and magnetic field variation (dH/dt) data measured at the Icheon geomagnetic observatory.

• Journal of The Korean Astronomical Society
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• v.36 no.spc1
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• pp.29-36
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• 2003

Quiescent solar radiation, at microwave spectral regime, is dominated by gyroresonant and thermal Bremsstrahlung radiations from hot electrons residing in solar active region corona. These radiations are known to provide excellent diagnostics on the coronal temperature, density, and magnetic field, provided that spatially resolved spectra are available from observations. In this paper we present an imaging spectroscopy implemented for a bipolar active region, AR 7912, using the multifrequency interferometric data from the Owens Valley Solar Array (OVSA), as processed with a new imaging technique, so-called Spatio-Spectral Maximum Entropy Method (SSMEM). From the microwave maps at 26 frequencies in the range of 1.2-12.4 GHz at both right- and left-circular polarizations, we construct spatially resolved brightness spectra in every reconstructed pixel of about 2 arcsec interval. These spectra allowed us to determine 2-D distribution of electron temperature, magnetic field of coronal base, and emission measure at the coronal base above the active region. We briefly compare the present result with existing studies of the coronal active regions.

• Publications of The Korean Astronomical Society
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• v.13 no.1 s.14
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• pp.181-208
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• 1998

We have analyzed the sunspot and aurora data recorded in Go-Ryer-Sa. We have collected 35 records of sunspot observations for 46 days, and 232 records of auroral observations. To objectively estimate the periods of the solar activity appearing in these records a method of calculating the one-dimensional power spectrum from inhomogeneous data is developed, and applied to the sunspot and auroral data. We have found statistically significant 10.5 and 10 year periodicities in the distributions of sunspot and aurora records, respectively. These periods are consistent with the well-known solar activity cycle. There are indications of the long-term variations, but the period is not certain. We have also calculated the cross-correlations between the sunspot and auroral data. In particular, we have divided the aurora data into several subgroups to study their nature. We conclude that the historical records of strong auroral activity correspond to non-recurrent magnetic storms related to the sunspots. On the other hand, the records of weak auroral activity are thought to be related with the recurrent magnetic storms which occur frequently due to the coronal hole near the sunspot minimum.

• Journal of The Korean Astronomical Society
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• v.50 no.4
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• pp.105-109
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• 2017

The well-known solar cycle controls almost the entire appearance of the solar photosphere. We therefore presume that the continuous emission of visible light from the solar surface follows the solar cyclic variation. In this study, we examine the solar cyclic variation of photospheric brightness in the visible range using solar images taken by the Solar and Heliospheric Observatory (SOHO)/Michelson Doppler Imager (MDI). The photospheric brightness in the visible range is quantified via the relative intensity acquired from in the raw solar images. In contrast to total solar irradiance, the relative intensity is out of phase with the solar cycle. During the solar minimum of solar cycles 23-24, the relative intensity shows enhanced heliolatitudinal asymmetry due to a positive asymmetry of the sunspot number. This result can be explained by the strength of the solar magnetic field that controls the strength of convection, implying that the emission in the visible range is controlled by the strength of convection. This agrees with the photospheric brightness increasing during a period of long spotless days.

• 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.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.6
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• pp.390-395
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• 2005

Sunspots are dark areas that grow and decay on the lowest level of the sun that is visible from the Earth. Shot-term predictions of solar activity are essential to help plan missions and to design satellites that will survive for their useful lifetimes. This paper presents a parallel-structure fuzzy system(PSFS) for prediction of sunspot number time series. The PSFS consists of a multiple number of component fuzzy systems connected in parallel. Each component fuzzy system in the PSFS predicts future data independently based on its past time series data with different embedding dimension and time delay. An embedding dimension determines the number of inputs of each component fuzzy system and a time delay decides the interval of inputs of the time series. According to the embedding dimension and the time delay, the component fuzzy system takes various input-output pairs. The PSFS determines the final predicted value as an average of all the outputs of the component fuzzy systems in order to reduce error accumulation effect.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.81.2-81.2
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• 2019

We develop an image-to-image translation model, which is a popular deep learning method based on conditional Generative Adversarial Networks (cGANs), to generate solar magnetograms and EUV images from sunspot drawings. For this, we train the model using pairs of sunspot drawings from Mount Wilson Observatory (MWO) and their corresponding SDO/HMI magnetograms and SDO/AIA EUV images (512 by 512) from January 2012 to September 2014. We test the model by comparing pairs of actual SDO images (magnetogram and EUV images) and the corresponding AI-generated ones from October to December in 2014. Our results show that bipolar structures and coronal loop structures of AI-generated images are consistent with those of the original ones. We find that their unsigned magnetic fluxes well correlate with those of the original ones with a good correlation coefficient of 0.86. We also obtain pixel-to-pixel correlations EUV images and AI-generated ones. The average correlations of 92 test samples for several SDO lines are very good: 0.88 for AIA 211, 0.87 for AIA 1600 and 0.93 for AIA 1700. These facts imply that AI-generated EUV images quite similar to AIA ones. Applying this model to the Galileo sunspot drawings in 1612, we generate HMI-like magnetograms and AIA-like EUV images of the sunspots. This application will be used to generate solar images using historical sunspot drawings.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.2
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• pp.45.3-46
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• 2018

Oscillations in a sunspot are easily detected through the Doppler velocity observation. Although the sunspot oscillations look erratic, the wavelet analysis show that they consist of successive wave packets which have strong power near three or five minutes. Previous studies found that 3-min oscillation at the chromosphere is a visual pattern of upward propagating acoustic waves along the magnetic field lines. Resent multi-height observations help this like vertical study, however, we also focus on horizontal facet to extend three dimensional understand of sunspot waves. So, we investigate a fragmented sunspot expected to have complex wave profiles according to the positions in the sunspot observed by the Fast Imaging Solar Spectrograph. We choose 4 points at different umbral cores as sampling positions to determine coherence of oscillations. The sets of cross-correlation with three and five minutes bandpass filters during a single wave packet reveal interesting results. Na I line show weak correlations with some lags, but Fe I and Ni I have strong correlations with no phase difference over the sunspots. It is more remarkable at Ni I line with 3-min bandpass that all sets of cross-correlation look like the autocorrelation. We can interpret this as sunspot oscillations occur spontaneously over a sunspot at photosphere but not at chromosphere. It implies a larger or deeper origin of 3-min sunspot oscillation.

• Journal of The Korean Astronomical Society
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• v.53 no.6
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• pp.139-147
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• 2020

The sunspot area is a critical physical quantity for assessing the solar activity level; forecasts of the sunspot area are of great importance for studies of the solar activity and space weather. We developed an innovative hybrid model prediction method by integrating the complementary ensemble empirical mode decomposition (CEEMD) and extreme learning machine (ELM). The time series is first decomposed into intrinsic mode functions (IMFs) with different frequencies by CEEMD; these IMFs can be divided into three groups, a high-frequency group, a low-frequency group, and a trend group. The ELM forecasting models are established to forecast the three groups separately. The final forecast results are obtained by summing up the forecast values of each group. The proposed hybrid model is applied to the smoothed monthly mean sunspot area archived at NASA's Marshall Space Flight Center (MSFC). We find a mean absolute percentage error (MAPE) and a root mean square error (RMSE) of 1.80% and 9.75, respectively, which indicates that: (1) for the CEEMD-ELM model, the predicted sunspot area is in good agreement with the observed one; (2) the proposed model outperforms previous approaches in terms of prediction accuracy and operational efficiency.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.40.3-40.3
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• 2019

Our recent observations of the Sun through strong spectral lines have revealed several important properties of the three-minute umbral oscillations inside sunspots -- the oscillations of intensity and Doppler velocity with periods of 2 to 3 minutes. The oscillations usually occur in the form of a time series of oscillation packets each of which lasts 10 to 20 minutes, not as continuous trains. Each oscillation packet is characterized by a singly peaked power spectrum of velocity oscillation. The oscillations propagate in the vertical direction from the photosphere to the corona. In the upper chromosphere, they develop into shocks that eventually collide with the transition region. When shocks propagate along a highly inclined direction, the merging of two successive shocks can take place. Once they enter the corona, they change to linear compressional waves. In the image plane, the three-minute oscillations propagate with high speeds in the transverse direction as well, usually propagating radially outwards from a point, and sometimes accompanying spiraling patterns of Doppler velocity. These observational properties can be theoretically explained by postulating the spatio-temporally localized source of fast MHD waves at a depth of about 2000 km below the surface, the excitation of slow MHD waves via mode conversion near the photosphere, and the resonance of the slow waves in the photospheric layer below the temperature minimum, and the nonlinear development of slow waves in the chromosphere.