• Journal of Astronomy and Space Sciences
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• v.36 no.3
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• pp.149-157
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• 2019

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 $Ni{\tilde{n}}o$ episodes are likely to occur around the solar maximum, but also explains why tropical cyclones occurring in the solar maximum periods and in El $Ni{\tilde{n}}o$ 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.

• Bulletin of the Korean Space Science Society
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• 2004.04a
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• pp.36-36
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• 2004

Ionospheric data from DGS-256 ionosonde operated by Radio Research Laboratory in Anyang archived during 1991-2002 was extracted and analyzed firstly in Korea. Daily, monthly and annual variations of the 12-year F2 layer critical frequency(foF2) are derived to investigate the statistical ionospheric characteristics during one complete solar cycle. Positive correlation between the mean values of 24-hourly monthly median foF2 and the monthly smoothed sunspot number(SSN) for the same period is found. (omitted)

• Publications of The Korean Astronomical Society
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• v.11 no.1
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• pp.263-277
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• 1996

We have intensively carried out numerical calculations on flare predictions from the solar activity data for photospheric sunspots, chromospheric flare and plages, coronal X-ray intensities and 2800MHz radio fluxes, by using multilinear regression method. Intensities of solar flares for the next day have been predicted from the solar data between 1977-1982 and 1993-1996. Firstly, we have calculated flare predictions with the multilinear regression method, by using separate solar data in growth and decay phase of sunspot area and magnetic field strength from the whole data on solar activities. Secondly, the same operations as above have been made for the remaining data after removal of the data with large deviation from the mean calculated by the above prediction method. we have reached a conclusion that average hit ratio of correct predictions to total predictions of flares with class of M5 over has been as high as 70% for the first case and that of correct prediction number to total observation number has been shown as 61%.

• Journal of The Korean Astronomical Society
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• v.40 no.4
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• pp.99-106
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• 2007

Statistical analyses were performed to investigate the relative success and accuracy of daily maximum X-ray flux (MXF) predictions, using both multilinear regression and autoregressive time-series prediction methods. As input data for this work, we used 14 solar activity parameters recorded over the prior 2 year period (1989-1990) during the solar maximum of cycle 22. We applied the multilinear regression method to the following three groups: all 14 variables (G1), the 2 so-called 'cause' variables (sunspot complexity and sunspot group area) showing the highest correlations with MXF (G2), and the 2 'effect' variables (previous day MXF and the number of flares stronger than C4 class) showing the highest correlations with MXF (G3). For the advanced three days forecast, we applied the autoregressive timeseries method to the MXF data (GT). We compared the statistical results of these groups for 1991 data, using several statistical measures obtained from a $2{\times}2$ contingency table for forecasted versus observed events. As a result, we found that the statistical results of G1 and G3 are nearly the same each other and the 'effect' variables (G3) are more reliable predictors than the 'cause' variables. It is also found that while the statistical results of GT are a little worse than those of G1 for relatively weak flares, they are comparable to each other for strong flares. In general, all statistical measures show good predictions from all groups, provided that the flares are weaker than about M5 class; stronger flares rapidly become difficult to predict well, which is probably due to statistical inaccuracies arising from their rarity. Our statistical results of all flares except for the X-class flares were confirmed by Yates' $X^2$ statistical significance tests, at the 99% confidence level. Based on our model testing, we recommend a practical strategy for solar X-ray flare predictions.

• Journal of Astronomy and Space Sciences
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• v.33 no.4
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• pp.279-285
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• 2016

The space radiation dose over air routes including polar routes should be carefully considered, especially when space weather shows sudden disturbances such as coronal mass ejections (CMEs), flares, and accompanying solar energetic particle events. We recently established a heliocentric potential (HCP) prediction model for real-time operation of the CARI-6 and CARI-6M programs. Specifically, the HCP value is used as a critical input value in the CARI-6/6M programs, which estimate the aviation route dose based on the effective dose rate. The CARI-6/6M approach is the most widely used technique, and the programs can be obtained from the U.S. Federal Aviation Administration (FAA). However, HCP values are given at a one month delay on the FAA official webpage, which makes it difficult to obtain real-time information on the aviation route dose. In order to overcome this critical limitation regarding the time delay for space weather customers, we developed a HCP prediction model based on sunspot number variations (Hwang et al. 2015). In this paper, we focus on improvements to our HCP prediction model and update it with neutron monitoring data. We found that the most accurate method to derive the HCP value involves (1) real-time daily sunspot assessments, (2) predictions of the daily HCP by our prediction algorithm, and (3) calculations of the resultant daily effective dose rate. Additionally, we also derived the HCP prediction algorithm in this paper by using ground neutron counts. With the compensation stemming from the use of ground neutron count data, the newly developed HCP prediction model was improved.

• Communications for Statistical Applications and Methods
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• v.25 no.4
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• pp.431-442
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• 2018

This paper highlights the computational explosion issues in the autoregressive moving average approach of frequency estimation of sinusoidal data with a large sample size. A new algorithm is proposed to circumvent the computational explosion difficulty in the conditional least-square estimation method. Notice that sinusoidal pattern can be generated by a non-invertible non-stationary autoregressive moving average (ARMA) model. The computational explosion is shown to be closely related to the non-invertibility of the equivalent ARMA model. Simulation studies illustrate the computational explosion phenomenon and show that the proposed algorithm can efficiently overcome computational explosion difficulty. Real data example of sunspot number is provided to illustrate the application of the proposed algorithm to the time series data exhibiting sinusoidal pattern.

• Bulletin of the Korean Space Science Society
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• 2009.10a
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• pp.26.1-26.1
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• 2009

Many solar, interplanetary and geomagnetic activity parameters have 11-year cycle on the average in sync with solar sunspot number. The galactic cosmic ray (GCR) intensity measured by ground Neutron Monitor (NM) is one of those parameters showing the unprecedented activity levels in the current solar minimum (2008-2009) of solar cycles 23/24. We defined abnormality as the ratio of deviation from long term mean over mean amplitude of solar cycle change. The abnormality distribution map was drawn using all the data of NM stations available online. The implications of those unprecedented levels of GCR intensities of different cutoff rigidities will be discussed.

• Journal of Advanced Navigation Technology
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• v.22 no.5
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• pp.409-414
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• 2018

Extrapolating the correction information of ionosphere is essential for expanding wide area differential GPS (WADGPS) service area beyond the reference station network. In this paper, design and analysis of the artificial neural network for expanding the ionospheric correction region will be proposed. First, analysis about influence of each input of neural network were performed. The inputs are the day/year periodic function, sunspot number, and geomagnetic index (Ap). Second, performance analysis with respect to the number of hidden layers and neurons in the neural network is shown. As a result, estimation of total electron contents (TEC) on the high/low latitude regions in solar max(2014) are displayed.

• Atmosphere
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• v.22 no.3
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• pp.381-386
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• 2012

The monthly number of days with rain or snow in Seoul extends backward to 1626 from the present. The number of rain and snow days are from the ancient records and combined with the modern precipitation records from 1907 to the present. There are two distinct and abrupt changes in the time series, which allow us to divide the entire period into three sub-periods of CR-I, CR-II, and MR. For each sub-period, we calculated the basic statistics and the associated distributions. The analysis proves Seoul, which may comprise East Asia when considering the lengthy period of dry condition, had dry climate for the Maunder Minimum when Europe experienced cold climate. We also note relationships between the rain days and sunspot numbers in various frequency bands.

• Journal of Astronomy and Space Sciences
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• v.30 no.2
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• pp.101-106
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• 2013

The length of solar cycle 23 has been prolonged up to about 13 years. Many studies have speculated that the solar cycle 23/24 minimum will indicate the onset of a grand minimum of solar activity, such as the Maunder Minimum. We check the trends of solar (sunspot number, solar magnetic fields, total solar irradiance, solar radio flux, and frequency of solar X-ray flare), interplanetary (interplanetary magnetic field, solar wind and galactic cosmic ray intensity), and geomagnetic (Ap index) parameters (SIG parameters) during solar cycles 21-24. Most SIG parameters during the period of the solar cycle 23/24 minimum have remarkably low values. Since the 1970s, the space environment has been monitored by ground observatories and satellites. Such prevalently low values of SIG parameters have never been seen. We suggest that these unprecedented conditions of SIG parameters originate from the weakened solar magnetic fields. Meanwhile, the deep 23/24 solar cycle minimum might be the portent of a grand minimum in which the global mean temperature of the lower atmosphere is as low as in the period of Dalton or Maunder minimum.