Forecast evaluation of the coronal mass ejection (CME) geoeffectiveness using halo CMEs from 1997 to 2003

Kim, Rok‐Soon; Cho, K.-S.; Moon, Yong‐Jae; Kim, Y.-H.; Yi, Yu; Dryer, M.; Bong, Su-Chan; Park, Y.-D.

doi:10.1029/2005ja011218

Cited by 69 publications

(48 citation statements)

References 29 publications

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“…In previous study, the classification with CME lo- Kernel Parameters : c(C = 2 c ), g(γ = 2 g ) (Kim et al 2005). When comparing these values, we found that the PODn and FAR of the SVM result are slightly lower, but PODy, Bias and CSI are significantly improved.…”

Section: Resultsmentioning

confidence: 96%

“…Earthward CMEs interact with the Earth's magnetic field and result in geomagnetic storms. There have been many studies on the relationship between CMEs and geomagnetic storms; front-side halo CME (Webb 2002;Gopalswamy et al 2007;Zhang et al 2007), the location of CMEs (Kim et al 2005;Wang et al 2002), the speed of CMEs (Srivastava & Venkatakrishnan 2004), and front-side direction parameter of CMEs (Moon et al 2005;Kim et al 2008).…”

Section: Introductionmentioning

confidence: 99%

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Application of Support Vector Machine to the Prediction of Geo-Effective Halo Cmes

Choi¹,

Moon²,

Vien³

et al. 2012

Journal of The Korean Astronomical Society

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In this study we apply Support Vector Machine (SVM) to the prediction of geo-effective halo coronal mass ejections (CMEs). The SVM, which is one of machine learning algorithms, is used for the purpose of classification and regression analysis. We use halo and partial halo CMEs from January 1996 to April 2010 in the SOHO/LASCO CME Catalog for training and prediction. And we also use their associated X-ray flare classes to identify front-side halo CMEs (stronger than B1 class), and the Dst index to determine geo-effective halo CMEs (stronger than -50 nT). The combinations of the speed and the angular width of CMEs, and their associated X-ray classes are used for input features of the SVM. We make an attempt to find the best model by using cross-validation which is processed by changing kernel functions of the SVM and their parameters. As a result we obtain statistical parameters for the best model by using the speed of CME and its associated X-ray flare class as input features of the SVM: Accuracy=0.66, PODy=0.76, PODn=0.49, FAR=0.72, Bias=1.06, CSI=0.59, TSS=0.25. The performance of the statistical parameters by applying the SVM is much better than those from the simple classifications based on constant classifiers.

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Section: Resultsmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

Application of Support Vector Machine to the Prediction of Geo-Effective Halo Cmes

Choi¹,

Moon²,

Vien³

et al. 2012

Journal of The Korean Astronomical Society

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“…Information about CMEs, their velocity and their place of origin on the solar surface enables geomagnetic activity to be forecast 1-3 days in advance (Srivastava 2005;Gleisner and Watermann 2006a, b), the source of the most severe geomagnetic disturbances being CMEs with the highest velocity (Tsurutani 2001;Kim et al 2005). However, the effects in the near-Earth environment critically depend on whether the interplanetary magnetic field in the post-shock solar wind rotates from North to South or vice versa.…”

Section: Predictability Of Space Weathermentioning

confidence: 99%

Space Weather: Physics, Effects and Predictability

2010

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The time varying conditions in the near-Earth space environment that may affect space-borne or ground-based technological systems and may endanger human health or life are referred to as space weather. Space weather effects arise from the dynamic and highly variable conditions in the geospace environment starting from explosive events on the Sun (solar flares), Coronal Mass Ejections near the Sun in the interplanetary medium, and various energetic effects in the magnetosphere-ionosphere-atmosphere system. As the utilization of space has become part of our everyday lives, and as our lives have become increasingly dependent on technological systems vulnerable to the space weather influences, the understanding and prediction of hazards posed by these active solar events have grown in importance. In this paper, we review the processes of the Sun-Earth interactions, the dynamic conditions within the magnetosphere, and the predictability of space weather effects on radio waves, satellites and ground-based technological systems today.

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“…Therefore, new opportunities to improve the scientific knowledge on the triggers of geomagnetic disturbances arise, leading to develop new forecasting tools based on solar observations. These solar-based tools (see e.g., Kim et al 2005;Gleisner & Watermann 2006a, 2006bRobbrecht & Berghmans 2006) are able to forecast in advance -one to three days depending on the solar wind speed -to those prediction schemes based on the knowledge of interplanetary parameters (see e.g., Boberg et al 2000;Gleisner & Lundstedt, 2001a, 2001bLundstedt et al 2002aLundstedt et al , 2002b. For practical applications the first can serve as a preliminary warning, which is then confirmed or cancelled by the latter.…”

Section: Response Of the Terrestrial Environment To Solar Activitymentioning

confidence: 99%

Geomagnetic response to solar and interplanetary disturbances

Sáiz

Cerrato

Cid

et al. 2013

J. Space Weather Space Clim.

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The space weather discipline involves different physical scenarios, which are characterised by very different physical conditions, ranging from the Sun to the terrestrial magnetosphere and ionosphere. Thanks to the great modelling effort made during the last years, a few Sun-to-ionosphere/thermosphere physics-based numerical codes have been developed. However, the success of the prediction is still far from achieving the desirable results and much more progress is needed. Some aspects involved in this progress concern both the technical progress (developing and validating tools to forecast, selecting the optimal parameters as inputs for the tools, improving accuracy in prediction with short lead time, etc.) and the scientific development, i.e., deeper understanding of the energy transfer process from the solar wind to the coupled magnetosphere-ionosphere-thermosphere system. The purpose of this paper is to collect the most relevant results related to these topics obtained during the COST Action ES0803. In an end-to-end forecasting scheme that uses an artificial neural network, we show that the forecasting results improve when gathering certain parameters, such as X-ray solar flares, Type II and/or Type IV radio emission and solar energetic particles enhancements as inputs for the algorithm. Regarding the solar wind-magnetosphere-ionosphere interaction topic, the geomagnetic responses at high and low latitudes are considered separately. At low latitudes, we present new insights into temporal evolution of the ring current, as seen by Burton's equation, in both main and recovery phases of the storm. At high latitudes, the PCC index appears as an achievement in modelling the coupling between the upper atmosphere and the solar wind, with a great potential for forecasting purposes. We also address the important role of small-scale field-aligned currents in Joule heating of the ionosphere even under non-disturbed conditions. Our scientific results in the framework of the COST Action ES0803 cover the topics from the short-term solar-activity evolution, i.e., space weather, to the long-term evolution of relevant solar/heliospheric/magnetospheric parameters, i.e., space climate. On the timescales of the Hale and Gleissberg cycles (22-and 88-year cycle respectively) we can highlight that the trend of solar, heliospheric and geomagnetic parameters shows the solar origin of the widely discussed increase in geomagnetic activity in the last century.

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Forecast evaluation of the coronal mass ejection (CME) geoeffectiveness using halo CMEs from 1997 to 2003

Cited by 69 publications

References 29 publications

Application of Support Vector Machine to the Prediction of Geo-Effective Halo Cmes

Application of Support Vector Machine to the Prediction of Geo-Effective Halo Cmes

Space Weather: Physics, Effects and Predictability

Geomagnetic response to solar and interplanetary disturbances

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