Automatic Determination of the Conic Coronal Mass Ejection Model Parameters

Pulkkinen, A.; Oates, Tim; Taktakishvili, A.

doi:10.1007/s11207-009-9473-z

Cited by 16 publications

(47 citation statements)

References 19 publications

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“…Recently Pulkkinen et al [2010] developed a novel method for the automatic determination of cone model parameters from coronagraph images. The method uses both standard image processing techniques to extract the CME extent from white light coronagraph images and a novel inversion routine providing the final cone parameters.…”

Section: Brief Description: Wsa‐enlil Cone Model Analytical and Automentioning

confidence: 99%

“…Importantly, this provides direct means for ensemble predictions of transient propagation in the heliosphere. An initial validation of the automatic method was carried out by Pulkkinen et al [2010] by means of comparison to analytically determined cone model parameters using the method of Xie et al [2004]. It was shown using 14 halo CME events that there is reasonable agreement, especially between the heliocentric locations of the cones derived with the two methods.…”

Section: Brief Description: Wsa‐enlil Cone Model Analytical and Automentioning

confidence: 99%

“…In our previous papers [ Taktakishvili et al , 2009, 2010] we presented the results of the WSA‐ENLIL cone modeling for 14 CME events and compared them to ACE observations and two reference model results. The WSA‐ENLIL cone model has three components: (1) Wang‐Shelley‐Arge model, which computes the solar wind speed and magnetic field at the bounding surface using an empirical relationship [ Arge and Pizzo , 2000]; (2) cone model for halo CMEs, an analytical [ Xie et al , 2004] or automatic [ Pulkkinen et al , 2010] method to determine the angular width, propagation orientation and radial velocity of halo CMEs; and (3) the ENLIL heliosphere model, a time‐dependent 3‐D MHD model of the heliosphere, developed by D. Odstrcil [see, e.g., Odstrcil and Pizzo , 1999; Odstrcil et al , 2004].…”

Section: Introductionmentioning

confidence: 99%

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Modeling of coronal mass ejections that caused particularly large geomagnetic storms using ENLIL heliosphere cone model

et al. 2011

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[1] In our previous paper we reported the results of modeling of 14 selected well-observed strong halo coronal mass ejection (CME) events using the WSA-ENLIL cone model combination. Cone model input parameters were obtained from white light coronagraph images of the CME events using the analytical method developed by Xie et al. (2004). This work verified that coronagraph input gives reasonably good results for the CME arrival time prediction. In contrast to Taktakishvili et al. (2009), where we started the analysis by looking for clear CME signatures in the data and then proceeded to model the interplanetary consequences at 1 AU, in the present paper we start by generating a list of observed geomagnetic storm events and then work our way back to remote solar observations and carry out the corresponding CME modeling. The approach used in this study is addressing space weather forecasting and operational needs. We analyzed 36 particularly strong geomagnetic storms, then tried to associate them with particular CMEs using SOHO/LASCO catalogue, and finally modeled these CMEs using WSA-ENLIL cone model. Recently, Pulkkinen et al. (2010) developed a novel method for automatic determination of cone model parameters. We employed both analytical and automatic methods to determine cone model input parameters. We examined the CME arrival times and magnitude of impact at 1 AU for both techniques. The results of the simulations are compared with the ACE satellite observations. This comparison demonstrated that WSA-ENLIL model combination with coronagraph input gives reasonably good results for the CME arrival times for this set of "geoeffective" CME events as well.Citation: Taktakishvili, A., A. Pulkkinen, P. MacNeice, M. Kuznetsova, M. Hesse, and D. Odstrcil (2011), Modeling of coronal mass ejections that caused particularly large geomagnetic storms using ENLIL heliosphere cone model, Space Weather, 9, S06002,

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Section: Brief Description: Wsa‐enlil Cone Model Analytical and Automentioning

confidence: 99%

Section: Brief Description: Wsa‐enlil Cone Model Analytical and Automentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Modeling of coronal mass ejections that caused particularly large geomagnetic storms using ENLIL heliosphere cone model

et al. 2011

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“…Using 2D images to determine parameters of a 3D structure, potentially causes projection effects [ Burkepile et al , 2004; Schwenn et al , 2005; Vršnak et al , 2007] and is more efficient in some cases than others. However, 2D SOHO/LASCO images in many cases provide the only available constraints, and are therefore often the basis of techniques developed to determine input parameters for CME models [ Zhao et al , 2002; Michałek et al , 2003; Xie et al , 2004; Pulkkinen et al , 2010]. The manual method presented by Xie et al [2004], which builds on the method presented by Zhao et al [2002], has often been used in combination with ENLIL, validating the simulations against near‐Earth satellite data [ Taktakishvili et al , 2009; Falkenberg et al , 2010; Vršnak et al , 2010] and near‐Earth and near‐Mars satellite data in combination [ Falkenberg et al , 2011].…”

Section: Introductionmentioning

confidence: 99%

Evaluating predictions of ICME arrival at Earth and Mars

Falkenberg¹,

Taktakishvili

Pulkkinen

et al. 2011

Space Weather

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[1] We present a study of interplanetary coronal mass ejection (ICME) propagation to Earth and Mars. Because of the significant space weather hazard posed by ICMEs, understanding and predicting their arrival and impact at Mars is important for current and future robotic and manned missions to the planet. We compare running ENLILv2.6 with coronal mass ejection (CME) input parameters from both a manual and an automated method. We analyze shock events identified at Mars in Mars Global Surveyor data in 2001 and 2003, when Earth and Mars were separated by <80°in heliocentric longitude. The shocks identified at Mars were also identified at Earth, and the majority of the shock sources were identified through the Solar and Heliospheric Observatory-Large Angle and Spectrometric Coronagraph catalogue. We find that arrival times predicted by the two methods at both planets are statistically similar, dynamic pressures predicted when using the automated method are better, and the automated method tends to underestimate both CME width and speed. Using the location of the related flare as the CME direction did not improve results. In addition, changing the CME speed toward the plane-of-sky speed at 20 R S improves the match to observations, mainly because the speed found by the automated method is underestimated. The time lapse between the shock arrival at Earth and Mars, for the events studied here, is shorter than expected from simulations, and the presence of high speed streams can enable an ICME to arrive almost simultaneously at Earth and Mars. This work will be applied to improve the input parameter methods for ENLIL.

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“…They have reported that their method is effective as a region of interest highlighter and a promising first step in autonomous heliospheric imager CME detections. To characterize the 3D structure of solar transients, Pulkkinen et al (2009) have introduced a method that allows for the automatic determination of cone model parameters from white-light coronagraph images. They reported that the proposed method shows reasonable agreement in CME parameter estimations using SOHO LASCO C3 difference images and can consequently become a part of a fully automatic CME detection and 3D characterization system.…”

Section: Introductionmentioning

confidence: 99%

Combining STEREO SECCHI COR2 and HI1 images for automatic CME front edge tracking

Kirnosov

Chang

Pulkkinen

2016

J. Space Weather Space Clim.

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COR2 coronagraph images are the most commonly used data for coronal mass ejection (CME) analysis among the various types of data provided by the STEREO (Solar Terrestrial Relations Observatory) SECCHI (Sun-Earth Connection Coronal and Heliospheric Investigation) suite of instruments. The field of view (FOV) in COR2 images covers 2-15 solar radii (Rs) that allow for tracking the front edge of a CME in its initial stage to forecast the lead-time of a CME and its chances of reaching the Earth. However, estimating the lead-time of a CME using COR2 images gives a larger lead-time, which may be associated with greater uncertainty. To reduce this uncertainty, CME front edge tracking should be continued beyond the FOV of COR2 images. Therefore, heliospheric imager (HI1) data that covers 15-90 Rs FOV must be included. In this paper, we propose a novel automatic method that takes both COR2 and HI1 images into account and combine the results to track the front edges of a CME continuously. The method consists of two modules: pre-processing and tracking. The pre-processing module produces a set of segmented images, which contain the signature of a CME, for both COR2 and HI1 separately. In addition, the HI1 images are resized and padded, so that the center of the Sun is the central coordinate of the resized HI1 images. The resulting COR2 and HI1 image set is then fed into the tracking module to estimate the position angle (PA) and track the front edge of a CME. The detected front edge is then used to produce a height-time profile that is used to estimate the speed of a CME. The method was validated using 15 CME events observed in the period from January 1, 2008 to August 31, 2009. The results demonstrate that the proposed method is effective for CME front edge tracking in both COR2 and HI1 images. Using this method, the CME front edge can now be tracked automatically and continuously in a much larger range, i.e., from 2 to 90 Rs, for the first time. These improvements can greatly help in making the quantitative CME analysis more accurate and have the potential to assist in space weather forecasting.

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Automatic Determination of the Conic Coronal Mass Ejection Model Parameters

Cited by 16 publications

References 19 publications

Modeling of coronal mass ejections that caused particularly large geomagnetic storms using ENLIL heliosphere cone model

Modeling of coronal mass ejections that caused particularly large geomagnetic storms using ENLIL heliosphere cone model

Evaluating predictions of ICME arrival at Earth and Mars

Combining STEREO SECCHI COR2 and HI1 images for automatic CME front edge tracking

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