• 한국우주과학회:학술대회논문집(한국우주과학회보)
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• 한국우주과학회 2006년도 한국우주과학회보 제15권2호
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• pp.53-53
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• 2006

• 천문학회보
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• 제32권1호
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• pp.86.1-86.1
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• 2007

• 천문학회지
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• 제34권4호
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• pp.317-319
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• 2001

The response of the earth's magnetosphere to the variation of the solar wind parameters and Interplanetary magnetic field (IMF) has been stud}ed by using a high-resolution, three-dimension magnetohydrodynamic (MHD) simulation when the WIND data of velocity Vx, plasma density, dynamic pressure, By and Bz every 1 minute were used as input. Large electrojet and magnetic storm which occurred on October 21 and 22 are reproduced in the simulation (fig. 1). We have studied the energy transfer and tail reconnect ion in association with geomagnetic storms.

• 천문학회보
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• 제37권2호
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• pp.123.1-123.1
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• 2012

We have compared near-real time Kp forecast models based on neural network (NN) and support vector machine (SVM) algorithms. We consider four models as follows: (1) a NN model using ACE solar wind data; (2) a SVM model using ACE solar wind data; (3) a NN model using ACE solar wind data and preliminary kp values from US ground-based magnetometers; (4) a SVM model using the same input data as model 3. For the comparison of these models, we estimate correlation coefficients and RMS errors between the observed Kp and the predicted Kp. As a result, we found that the model 3 is better than the other models. The values of correlation coefficients and RMS error of the model 3 are 0.93 and 0.48, respectively. For the forecast evaluation of models for geomagnetic storms ($Kp{\geq}6$), we present contingency tables and estimate statistical parameters such as probability of detection yes (PODy), false alarm ratio (FAR), bias, and critical success index (CSI). From a comparison of these statistical parameters, we found that the SVM models (model 2 and model 4) are better than the NN models (model 1 and model 3). The values of PODy and CSI of the model 4 are the highest among these models (PODy: 0.57 and CSI: 0.48). From these results, we suggest that the NN models are better than the SVM models for predicting Kp and the SVM models are better than the NN models for forecasting geomagnetic storms.

• Journal of Astronomy and Space Sciences
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• 제24권4호
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• pp.269-274
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• 2007

강한 지자기 폭풍이 발생하였을 때 한반도 상공의 전리층내 총전자수(TEC, Total Electron Contents) 변화를 분석하기 위해 GPS 기준국망을 데이터를 이용한 지역적인 전리층 감시모델을 개발하였다. 전리층 총전자수 감시모델 개발을 위해 한국천문연구원에서 운용중인 대전 IGS(International GNSS Service) 기준국을 포함한 전국에 고르게 분포하고 있는 9개의 GPS 기준국 데이터를 이용하였다. 또한 순간적인 전리층 변화 특성을 분석하기 위해 CSS(Cubic Spline Smoothing)기법을 적용하였고, 그 결과 2003년 11월 20일 강한 지자기 폭풍이 발생했을 때 한반도 상공에서 총전자수의 순간적인 변화를 검출할 수 있었다. 이때에는 평일과 비교했을 때 특정시각의 약 1.5배 이상 총전자수가 증가함을 보였다. 마지막으로 지구 자기장 활동 정도를 나타내는 Kp 지수, Dst 지수 그리고 천문연 GPS 기준국망 데이터를 이용해 산출된 총전자수 변화와의 연관성을 제시했다.

• Journal of Astronomy and Space Sciences
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• 제34권4호
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• pp.315-330
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• 2017

Halo coronal mass ejections (CMEs) originating from solar activities give rise to geomagnetic storms when they reach the Earth. Variations in the geomagnetic field during a geomagnetic storm can damage satellites, communication systems, electrical power grids, and power systems, and induce currents. Therefore, automated techniques for detecting and analyzing halo CMEs have been eliciting increasing attention for the monitoring and prediction of the space weather environment. In this study, we developed an algorithm to sense and detect halo CMEs using large angle and spectrometric coronagraph (LASCO) C3 coronagraph images from the solar and heliospheric observatory (SOHO) satellite. In addition, we developed an image processing technique to derive the morphological and dynamical characteristics of halo CMEs, namely, the source location, width, actual CME speed, and arrival time at a 21.5 solar radius. The proposed halo CME automatic analysis model was validated using a model of the past three halo CME events. As a result, a solar event that occurred at 03:38 UT on Mar. 23, 2014 was predicted to arrive at Earth at 23:00 UT on Mar. 25, whereas the actual arrival time was at 04:30 UT on Mar. 26, which is a difference of 5 hr and 30 min. In addition, a solar event that occurred at 12:55 UT on Apr. 18, 2014 was estimated to arrive at Earth at 16:00 UT on Apr. 20, which is 4 hr ahead of the actual arrival time of 20:00 UT on the same day. However, the estimation error was reduced significantly compared to the ENLIL model. As a further study, the model will be applied to many more events for validation and testing, and after such tests are completed, on-line service will be provided at the Korean Space Weather Center to detect halo CMEs and derive the model parameters.

• 천문학회지
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• 제37권4호
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• pp.151-157
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• 2004

It is investigated quantitative relations between the magnetic storm magnitude and the solar wind parameters such as the Interplanetary Magnetic Field (hereinafter, IMF) magnitude (B), the southward component of IMF (Bz), and the dynamic pressure during the main phase of the magnetic storm with focus on the role of the interplanetary shock (hereinafter, IPS) in order to build the space weather fore-casting model in the future capable to predict the occurrence of the magnetic storm and its magnitude quantitatively. Total 113 moderate and intense magnetic storms and 189 forward IPSs are selected for four years from 1998 to 2001. The results agree with the general consensus that solar wind parameter, especially, Bz component in the shocked gas region plays the most important role in generating storms (Tsurutani and Gonzales, 1997). However, we found that the correlations between the solar wind parameters and the magnetic storm magnitude are higher in case the storm happens after the IPS passing than in case the storm occurs without any IPS influence. The correlation coefficients of B and $BZ_(min)$ are specially over 0.8 while the magnetic storms are driven by IPSs. Even though recently a Dst prediction model based on the real time solar wind data (Temerin and Li, 2002) is made, our correlation test results would be supplementary in estimating the prediction error of such kind of model and in improving the model by using the different fitting parameters in cases associated with IPS or not associated with IPS rather than single fitting parameter in the current model.

• 한국우주과학회:학술대회논문집(한국우주과학회보)
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• 한국우주과학회 2008년도 한국우주과학회보 제17권2호
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• pp.24.1-24.1
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• 2008

We examine the eccentricity parameter (EP) of Coronal Mass Ejections (CMEs). For this, we select 298 front-side CMEs from SOHO LASCO CMEs whose speed is larger than 1000km/s and angular width is greater than $120^{\circ}$ during from 1997 to 2007. These are thought to be the most plausible candidate of geoeffective CMEs. We examine the relation between CMEs eccentricity parameter and the minimum value of the Dst index. We find that strong geomagnetic storms (Dst < -200nT) are well correlated with the EP from the scattered plot. We also find that CMEs have high geoeffectiveness when they occurred near the center of the solar disk with the small EP and they have the small speed with the small EP. These results indicate that the CME EP also can be an important indicator to forecast CME geoeffectiveness such as Earthward direction parameter (Moon et al. 2005, Kim et al. 2008).

• Journal of Astronomy and Space Sciences
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• 제20권2호
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• pp.109-122
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• 2003

자기폭풍(magnetic storm)과 서브스톰(substorm)의 인과관계를 규명하기 위하여 서브스톰 확장기 활동(substorm expansive activity)의 전형적인 지시자로 알려진 정지궤도 위성에서 관측된 양성자 플럭스(proton flux)의 무분산 입자유입률(dispersionless particle injection rate)과 Dst 지수와의 상관관계를 조사하였다. 본 연구에 이용된 자기폭풍은 1996년에서 2000년까지 5년 동안에 일어난 것으로 자기폭풍 기간 중 Dst의 최소값인 $Dst_{min}$의 크기에 따라 대규모($-200nT{$\leq$}Dst_{min}{$\leq$}-100nT$), 중규모($-100nT{\leq}Dst_{min}{\leq}-50nT$), 소규모 자기폭풍($-50nT{\leq}Dst_{min}{\leq}-30nT$)의 3단계로 구분하였다. 양성자 플럭스는 LANL의 정지궤도 위성에서 관측된 자료 중에서 주로 환전류(ring current)를 구성하는 입자의 에너지에 해당하는 50keV에서 670keV 범위의 6개 에너지 채널의 자료를 이용하였다. 그리고 입자유입은 자정 부근에서 주로 일어나므로 18:00~04:00MLT구간에서 관측된 자료만을 이용하였다. 한편 내부 자기권으로 유입되는 입자에너지를 추정하기 위하여 양성자 플럭스 비($f_{max}/f_{ave}$)를 조사하였다. 여기서, $f_{ave}$ 및 $f_{max}$는 각각 입자유입이 일어나기 전 후의 양성자 플럭스의 양을 나타낸다. 한편 자기폭풍 기간 동안에 1 ~ 2개의 인공위성 관측으로부터 내부 자기권으로 유입되는 총 에너지량을 추정하는 것이 불가능하다는 것이 알려졌다. 그러나 총 에너지 유입량은 적어도 플럭스 비와 유입횟수에 비례할 것이다. 따라서 내부 자기권으로 유입되는 에너지의 양을 간접적으로 추정하기 위해서 이들의 곱으로 정의되는 총 에너지 유입률 지수(total energy injection parameter, TEIP)를 제안하였다. 특히 서브스톰이 자기폭풍의 발달에 기여하는 정도를 알기 위하여 자기폭풍을 두 구간, 즉 주상(main phase)과 회복기(recovery phase)로 나누어 조사하였다. 양성자의 무분산 유입자료와 자기폭풍 기간 중 Dst$_{min}$ 값을 비교해 본 결과 다음과 같은 특성이 확인되었다. 첫째, 주상기간 중 입자들의 평균 유입횟수는 자기폭풍의 크기에 비례하여 증가하는 경향을 나타내며 유입휫수와 $Dst_{min}$ 사이에는 높은 상관관계(0.83)가 있었다. 둘째, 주상기간 중 자기폭풍의 크기가 클수록 플럭스 비 ($f_{max}/f_{ave}$는 대체로 증가하는 경향을 나타냈다. 그리고 75~113keV 에너지 채널에서의 $Dst_{min}$ 값과 플럭스 비의 상관계수는 0.74로서 가장 높았으며 나머지 에너지 채널 역시 비교적 높은 상관관계를 나타냈다. 셋째, 주상기간 중 총 에너지 유입률 지수와 $Dst_{min}$ 사이에 높은 상관관계가 확인되었다. 특히 환전류를 구성하는 주요 입자의 에너지 영역(75~l13keV)에서 가장 높은(0.80) 상관계수를 기록했다. 넷째, 회복기 중에 일어나는 입자들의 유입은 자기폭풍의 지속시간을 연장시키는 경향을 보이며 큰 자기폭풍일수록 현저했다. 주상에서 관측된 이러한 특성은 서브스톰 확장기 활동이 자기폭풍의 발달과 밀접한 관계가 있음을 시사한다.

• Journal of Astronomy and Space Sciences
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• 제39권4호
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• pp.159-167
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• 2022

Because of the small number of spacecraft available in the Earth's magnetosphere at any given time, it is not possible to obtain direct measurements of the fundamental quantities, such as the magnetic field and plasma density, with a spatial coverage necessary for studying, global magnetospheric phenomena. In such cases, empirical as well as physics-based models are proven to be extremely valuable. This requires not only having high fidelity and high accuracy models, but also knowing the weakness and strength of such models. In this study, we assess the accuracy of the widely used Tsyganenko magnetic field models, T96, T01, and T04, by comparing the calculated magnetic field with the ones measured in-situ by the GOES satellites during geomagnetically disturbed times. We first set the baseline accuracy of the models from a data-model comparison during the intervals of geomagnetically quiet times. During quiet times, we find that all three models exhibit a systematic error of about 10% in the magnetic field magnitude, while the error in the field vector direction is on average less than 1%. We then assess the model accuracy by a data-model comparison during twelve geomagnetic storm events. We find that the errors in both the magnitude and the direction are well maintained at the quiet-time level throughout the storm phase, except during the main phase of the storms in which the largest error can reach 15% on average, and exceed well over 70% in the worst case. Interestingly, the largest error occurs not at the Dst minimum but 2-3 hours before the minimum. Finally, the T96 model has consistently underperformed compared to the other models, likely due to the lack of computation for the effects of ring current. However, the T96 and T01 models are accurate enough for most of the time except for highly disturbed periods.