• 천문학회보
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• 제38권2호
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• pp.33-33
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• 2013

We are developing empirical space weather (solar flare, solar proton event, and geomagnetic storm) forecast models based on solar data. In this talk we will review our main results and recent progress. First, we have examined solar flare (R) occurrence probability depending on sunspot McIntosh classification, its area, and its area change. We find that sunspot area and its increase (a proxy of flux emergence) greatly enhance solar flare occurrence rates for several sunspot classes. Second, a solar proton event (S) forecast model depending on flare parameters (flare strength, duration, and longitude) as well as CME parameters (speed and angular width) has been developed. We find that solar proton event probability strongly depends on these parameters and CME speed is well correlated with solar proton flux for disk events. Third, we have developed an empirical storm (G) forecast model to predict probability and strength of a storm using halo CME - Dst storm data. For this we use storm probability maps depending on CME parameters such as speed, location, and earthward direction. We are also looking for geoeffective CME parameters such as cone model parameters and magnetic field orientation. We find that all superstorms (less than -200 nT) occurred in the western hemisphere with southward field orientations. We have a plan to set up a storm forecast method with a three-stage approach, which will make a prediction within four hours after the solar coronagraph data become available. We expect that this study will enable us to forecast the onset and strength of a geomagnetic storm a few days in advance using only CME parameters and the WSA-ENLIL model. Finally, we discuss several ongoing works for space weather applications.

• 천문학회보
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• 제36권2호
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• pp.90.1-90.1
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• 2011

We are developing empirical space weather (geomagnetic storms, solar proton events, and solar flares) forecast models based on solar information. These models have been set up with the concept of probabilistic forecast using historical events. Major findings can be summarized as follows. First, we present a concept of storm probability map depending on CME parameters (speed and location). Second, we suggested a new geoeffective CME parameter, earthward direction parameter, directly observable from coronagraph observations, and demonstrated its importance in terms of the forecast of geomagnetic storms. Third, the importance of solar magnetic field orientation for storm occurrence was examined. Fourth, the relationship among coronal hole-CIR-storm relationship has been investigated, Fifth, the CIR forecast based on coronal hole information is possible but the storm forecast is challenging. Sixth, a new solar proton event (flux, strength, and rise time) forecast method depending on flare parameters (flare strength, duration, and longitude) as well as CME parameter (speed, angular width, and longitude) has been suggested. Seventh, we are examining the rates and probability of solar flares depending on sunspot McIntosh classification and its area change (as a proxy of flux change). Our results show that flux emergence greatly enhances the flare probability, about two times for flare productive sunspot regions.

• 천문학회보
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• 제38권1호
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• pp.63.1-63.1
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• 2013

To improve the forecast capability of geomagnetic storms, we consider the real time solar and near Earth conditions together, since the characteristics of CMEs can be modified during their transit from the Sun to the Earth, and the geomagnetic storms may be directly affected by not only solar events but also near Earth interplanetary conditions. Using 55 CME-Dst pairs associated with M- and X-class solar flares, which have clearly identifiable source regions during 1997 to 2003, we confirm that the peak values of negative magnetic field Bz and duskward electric field Ey prior to Dst minimum are strongly related with Dst index. We suggest the solar wind criteria (Bz<-5 nT or Ey>3 mV/m for t>2 hr) for moderate storm less than -50 nT by modifying the criteria for intense storms less than -100 nT proposed by Gonzalez and Tsurutani (GT, 1987). As the results, 90% (28/31) of the storms are correctly forecasted by our criteria. For 15 exceptional events that are incorrectly forecasted by only CME parameters, 12 cases (80%) can be properly forecasted by solar wind criteria. When we applying CME and solar wind conditions together, all geomagnetic storms (Dst<-50 nT) are correctly forecasted. Our results show that, the storm forecast capability of the 2~3 days advanced warning based on CME parameters can be improved by combining with the urgent warning based on the near Earth solar wind condition.

• 천문학회지
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• 제50권2호
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• pp.29-39
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• 2017

We investigate two abnormal CME-Storm pairs that occurred on 2014 September 10 - 12 and 2015 March 15 - 17, respectively. The first one was a moderate geomagnetic storm ($Dst_{min}{\sim}-75nT$) driven by the X1.6 high speed flare-associated CME ($1267km\;s^{-1}$) in AR 12158 (N14E02) near solar disk center. The other was a very intense geomagnetic storm ($Dst_{min}{\sim}-223nT$) caused by a CME with moderate speed ($719km\;s^{-1}$) and associated with a filament eruption accompanied by a weak flare (C9.1) in AR 12297 (S17W38). Both CMEs have large direction parameters facing the Earth and southward magnetic field orientation in their solar source region. In this study, we inspect the structure of Interplanetary Flux Ropes (IFRs) at the Earth estimated by using the torus fitting technique assuming self-similar expansion. As results, we find that the moderate storm on 2014 September 12 was caused by small-scale southward magnetic fields in the sheath region ahead of the IFR. The Earth traversed the portion of the IFR where only the northward fields are observed. Meanwhile, in case of the 2015 March 17 storm, our IFR analysis revealed that the Earth passed the very portion where only the southward magnetic fields are observed throughout the passage. The resultant southward magnetic field with long-duration is the main cause of the intense storm. We suggest that 3D magnetic field geometry of an IFR at the IFR-Earth encounter is important and the strength of a geomagnetic storm is strongly affected by the relative location of the Earth with respect to the IFR structure.

• 한국우주과학회:학술대회논문집(한국우주과학회보)
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• 한국우주과학회 2008년도 한국우주과학회보 제17권1호
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• pp.22.2-22.2
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• 2008

• Journal of Astronomy and Space Sciences
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• 제26권3호
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• pp.305-316
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• 2009

이 연구에서 우리는 코로나 홀(Coronal hole, CH)의 정보(위치, 면적)를 이용하여 CIR(Corotating Interaction Regions)과 지자기폭퐁(Geomagnetic Storm)에 대한 경험적인 예보를 수행하였다. 이것을 위해 1996년 1월 $\sim$ 2003년 11월까지의 미국 국립 천문대-Kitt Peak 관측소의 He I $1083{\AA}$ 영상으로부터 코로나 홀 자료를 얻고, Choi et al.(2009)로부터 확인된 CIR과 지자기폭풍 자료를 활용하였다. 지자기 폭풍을 일으키는 코로나 홀의 특성을 고려하여 코로나 홀의 중심이 $N40^{\circ}$와 $S40^{\circ}$ 사이, $E40^{\circ}$와 $W20^{\circ}$ 사이에 위치하고 태양 반구에 대한 면적 비율이 다음과 같은 세 가지 경우를 선택하였다: (1) case 1: 0.36% 이상, (2) case 2: 0.66% 이상, (3) case 3: $1996{\sim}2000$년 동안에는 0.36%, $2001{\sim}2003$년 동안에는 0.66% 이상. 우리는 각 경우에 대하여 예보의 성공 유무를 확인할 수 있는 예보 분할표(Contingency Table)를 만들고, 그들의 태양 주기 위상(Solar cycle phase)에 대한 의존성을 조사하였다 분할표로부터 우리는 PODy(the probability of detection yes), FAR(the false alarm ratio), Bias(the ratio of "yes" predictions to "yes" observations) 그리고 CSI(critical success index)와 같은 예보 평가 지수를 결정하였다. 이와 같은 예보에서 PODy와 CSI가 상대적으로 더 중요한 사실을 고려하여, 우리는 가장 좋은 후보가 case 3이라는 것을 발견하였다. 이 경우에 두 가지 예보에 대한 예보평가 지수는 아래와 같다: CH-CIR의 경우는 PODy=0.77, FAR=0.66, Bias=2.28, CSI=0.30이고, CH-storm의 경우는 PODy=0.81, FAR=0.84, Bias=5.00, CSI=0.16이다. 또한 태양 활동 극대기 이후 감쇄기간 동안의 지수들이 태양 극대기 이전의 값들 보다 훨씬 잘 예보되고 있음을 알 수 있다. 따라서 코로나 홀을 이용한 CIR의 예보는 충분한 가능성을 보여주고 있으나, 지자기 폭풍의 예보는 너무 많은 허위 예보로 인하여 다소 어려울 것으로 비상된다.

• Journal of Astronomy and Space Sciences
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• 제31권2호
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• pp.149-157
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• 2014

As the prediction of geomagnetic storms is becoming an important and practical problem, conditions in the Earth's magnetosphere have been studied rigorously in terms of those in the interplanetary space. Another approach to space weather forecast is to deal with it as a probabilistic geomagnetic storm forecasting problem. In this study, we carry out detailed statistical analysis of solar wind parameters and geomagnetic indices examining the dependence of the distribution on the solar cycle and annual variations. Our main findings are as follows: (1) The distribution of parameters obtained via the superimposed epoch method follows the Gaussian distribution. (2) When solar activity is at its maximum the mean value of the distribution is shifted to the direction indicating the intense environment. Furthermore, the width of the distribution becomes wider at its maximum than at its minimum so that more extreme case can be expected. (3) The distribution of some certain heliospheric parameters is less sensitive to the phase of the solar cycle and annual variations. (4) The distribution of the eastward component of the interplanetary electric field BV and the solar wind driving function BV2, however, appears to be all dependent on the solar maximum/minimum, the descending/ascending phases of the solar cycle and the equinoxes/solstices. (5) The distribution of the AE index and the Dst index shares statistical features closely with BV and $BV^2$ compared with other heliospheric parameters. In this sense, BV and $BV^2$ are more robust proxies of the geomagnetic storm. We conclude by pointing out that our results allow us to step forward in providing the occurrence probability of geomagnetic storms for space weather and physical modeling.

• 천문학회보
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• 제42권1호
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• pp.41.1-41.1
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• 2017

It is well known that there are good relations of coronal hole (CH) parameters such as the size, location, and magnetic field strength to the solar wind conditions and the geomagnetic storms. Especially in the minimum phase of solar cycle, CHs in mid- or low-latitude are one of major drivers for geomagnetic storms, since they form corotating interaction regions (CIRs). By adopting the method of Vrsnak et al. (2007), the Space Weather Research Center (SWRC) in Korea Astronomy and Space Science Institute (KASI) has done daily forecast of solar wind speed and Dst index from 2010. Through years of experience, we realize that the geomagnetic storms caused by CHs have different characteristics from those by CMEs. Thus, we statistically analyze the characteristics and causality of the geomagnetic storms by the CHs rather than the CMEs with dataset obtained during the solar activity was very low. For this, we examine the CH properties, solar wind parameters as well as geomagnetic storm indices. As the first result, we show the different trends of the solar wind parameters and geomagnetic indices depending on the degree of solar activity represented by CH (quiet) or sunspot number (SSN) in the active region (active) and then we evaluate our forecasts using CH information and suggest several ideas to improve forecasting capability.

• 천문학회보
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• 제35권2호
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• pp.51.2-51.2
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• 2010

We have investigated 63 intense geomagnetic storms (Dst $\leq$ -100 nT) that occurred from 1998 to 2006. Using these events, we compared Dst forecast models: Burton et al. (1975), Fenrich and Luhmann (1998), O'Brien and McPherron (2000a), Wang et al. (2003), and Temerin and Li (2002, 2006) models. For comparison, we examined a linear correlation coefficient, RMS error, the difference of Dst minimum value (${\Delta}$peak), and the difference of Dst minimum time (${\Delta}$peak_time) between the observed and the predicted during geomagnetic storm period. As a result, we found that Temerin and Li model is mostly much better than other models. The model produces a linear correlation coefficient of 0.94, a RMS (Root Mean Square) error of 14.89 nT, a MAD (Mean Absolute Deviation) of ${\Delta}$peak of 12.54 nT, and a MAD of ${\Delta}$peak_time of 1.44 hour. Also, we classified storm events as five groups according to their interplanetary origin structures: 17 sMC events (IP shock and MC), 18 SH events (sheath field), 10 SH+MC events (Sheath field and MC), 8 CIR events, and 10 nonMC events (non-MC type ICME). We found that Temerin and Li model is also best for all structures. The RMS error and MAD of ${\Delta}$peak of their model depend on their associated interplanetary structures like; 19.1 nT and 16.7 nT for sMC, 12.5 nT and 7.8 nT for SH, 17.6 nT and 15.8 nT for SH+MC, 11.8 nT and 8.6 nT for CIR, and 11.9 nT and 10.5 nT for nonMC. One interesting thing is that MC-associated storms produce larger errors than the other-associated ones. Especially, the values of RMS error and MAD of ${\Delta}$peak of SH structure of Temerin and Li model are very lower than those of other models.

• 천문학회보
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• 제34권1호
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• pp.81.2-81.2
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• 2009