Auto-detection of Halo CME Parameters as the Initial Condition of Solar Wind Propagation

To detect the eruption of a halo CME, an original LASCO C3 image at the time of interest (t) and an image of previous time step (t−1) are converted into a monochrome image.Fig. 2

Fig. 2. Example of converting original image into monochrome image (Image source: https://sohowww.nascom.nasa.gov//data/REPROCESSING/Completed/).

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In addition to halo CMEs, LASCO C3 images have background noise, and halo CMEs can be identified easily without such noise. To remove the noise, two monochrome images are utilized to generate an RDIFF image. The RDIFF image is used to remove the background field easily. Unlike with CMEs, the background field does not change significantly over time. An example of a background field is the continual release of solar wind from the sun. As shown in Fig. 3, a LASCO C3 image taken at 17:18 on Apr. 4, 2000 and an image of the previous time step at 16:43 were converted into monochrome images, and an RDIFF image of 17:18 was obtained from the difference between the two images. In this RDIFF image, the CME can be identified more easily compared to the monochrome images because the background field was removed to highlight the CME shapes. In addition, we can identify superfluous regions around the solar perimeter and the image boundary from this RDIFF image. This can also be identified in the original image or in a monochrome image. Once the superfluous regions are identified, only the regions of interest are extracted for subsequent processing. To remove the unnecessary regions, the center of the image is identified, and the regions of interest are extracted in reference to this center to conduct the subsequent process. As shown in Fig. 4, unnecessary regions are processed to appear in black, and in the subsequent process, the image processing is applied only for non-black regions.

Fig. 3. RDIFF images from two monochrome images (Image source: https://sohowww.nascom.nasa.gov//data/REPROCESSING/Completed/).

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Fig. 4. Required area only data of RDIFF image (Image source: https://sohowww.nascom.nasa.gov//data/REPROCESSING/ Completed/).

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To remove only noise from RDIFF images, while leaving the CME shapes untouched, various filtering techniques were applied and tested. This process is called the primary noise removal. The filtering techniques tested are the median technique, smoothing technique, and Lee filter technique, as described below.

With the median and smoothing techniques, the amount of removable noise can be adjusted by modifying the kernel size on the image, whereas with the Lee filter technique, the amount of noise can be adjusted by changing the size of the filter box. The amount of noise removed is proportional to the sizes of the kernel and filter box. When adjusting the size of the kernel or filter box, the optimal size required to remove noise only from the image, while leaving the CME shape untouched, is determined through trial and error. In this study, a kernel size ranging from 5 to 15 was tested for the median or smoothing technique, whereas the filter box size ranging from 5 to 15 was tested for the Lee filter technique. The test results indicate that the optimal size of both the kernel and filter box to remove only noise without affecting the CME shape is 11. These three techniques were applied for RDIFF images, as shown in Figs. 5, 6, and 7. As a result, it was found that the noise was removed in the CME shape of an RDIFF image. However, the degree of noise removal differs depending on the technique applied. In particular, it is possible to visually identify noise in the lower left area of the image for both the smoothing and Lee filter techniques. Thus, according to the application results of the three filtering techniques to the RDIFF images considered in this study, it was found that the median technique is most effective at removing noise when compared to the smoothing and Lee filter techniques.

Fig. 5. RDIFF image (left), and RDIFF image with median technique applied (right) (Image source: https://sohowww.nascom.nasa.gov//data/REPROCESSING/Completed/).

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Fig. 6. RDIFF image (left), and RDIFF image with smoothing applied (right) (Image source: https://sohowww.nascom.nasa.gov//data/REPROCESSING/Completed/).

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Fig. 7. RDIFF image (left), and RDIFF image with Lee filter applied (right) (Image source: https://sohowww.nascom.nasa.gov//data/REPROCESSING/Completed/).

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To discern CME shapes visually from RDIFF images with the primary noise removed, we analyzed the pixels of the CME shapes in the images. The threshold value, which is the minimum pixel value of a CME shape, is determined based on an analysis of 17 halo CME events erupted during the period of 2000 to 2015. Information on these 17 halo CMEs is summarized in Table 1. According to the analysis results of previous halo CME events, it was found that the pixel values of the CME shapes in the RDIFF images are greater than 4. Hence, the threshold value of the CME shapes is determined to be 4 in the RDIFF images. To distinguish CME shapes in the RDIFF images with the primary noise removed, a masking image processing technique was applied, and pixels with values of greater than 4 were considered as belonging to CME shapes.

Fig. 8. RDIFF image with primary noise (left), and extracted CME image (right) (Image source: https://sohowww.nascom.nasa.gov//data/REPROCESSING/Completed/).

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Fig. 9. RDIFF image with primary noise removed using median technique (left), and extracted CME image (right) (Image source: https://sohowww.nascom.nasa.gov//data/REPROCESSING/ Completed/).

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Fig. 10. RDIFF image with the primary noise removed using median technique (left), extracted CME shape (middle), and CME shape extraction result with the secondary noise removed (right) (Image source: https://sohowww.nascom.nasa.gov//data/REPROCESSING/Completed/).

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Fig. 11. Smoothed RDIFF image with the primary noise removed (left), extracted CME shape (middle), and CME shape extraction result with the secondary noise removed (right) (Image source: https://sohowww.nascom.nasa.gov//data/REPROCESSING/Completed/).

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Fig. 12. RDIFF image with Lee filter technique applied to remove primary noise (left), extracted CME shape (middle), and CME shape extraction result with the secondary noise removed (right) (Image source: https://sohowww.nascom.nasa.gov//data/REPROCESSING/Completed/).

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According to LASCO C3 images, halo CMEs heading toward Earth propagate radially from the center of the sun. In other words, the erupted halo CMEs are emitted almost circling the sun. Based on this feature, to distinguish a halo CME, the radial boundary of the CME shapes extracted from the image, that is, the interface, is determined. When the angular distribution of the interface for a CME shape is greater than Δ90˚, it is defined as a halo CME. The interface is determined after converting the Cartesian coordinate system [x, y] of the CME shapes extracted from the LASCO C3 images into a polar coordinate system [r, θ]. Fig. 13 shows a CME shape (red) extracted from an RDIFF image with median filtering applied (left-side image), with the radial boundary from the solar center, that is, the CME interface, shown in blue. The CME shape extracted from the RDIFF image in Cartesian coordinates is converted into polar coordinates, and the interface of the CME is defined as the pixel with the largest r value for each θ. The black dots in the right-side image of Fig. 13 indicate the interface. In this case, the interface is formed over angles of 75–360° and 0–20°, and the angular distribution is Δ305°, which is greater than Δ90°, and thus this CME is identified as a halo CME.

Fig. 13. Example of converting CME interface into polar coordinate system (Image source: https://sohowww.nascom.nasa.gov//data/ REPROCESSING/Completed/).

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When a CME is determined to be a halo CME, morphological parameters are produced by applying the cone model to the CME interface. The cone model assumes that the halo CME is a cone shape in order to determine its angular width and propagation orientation, as proposed by Xie et al. (2004). In this model, three coordinate systems are introduced.

The direction of the cone indicates the direction of propagation.

An intermediate coordinate system used to convert the heliocentric coordinate system into an apex-centered right cone coordinate system.

The morphological characteristics of the cone are represented by the longitude α (or ϕ), latitude θt (or λ), and angular width 2ω. Here, (ϕ, λ) indicates the longitude and latitude at the ecliptic plane, and (α, θ) indicates the longitude and latitude at the POS to conveniently determine the cone parameters; in addition, α is the angle between the xh-axis and the cone axis projected on the POS, and θ is the angle between the cone axis and the POS. In other words, the position of the halo CME, and α, θ, ϕ, λ, and ω, indicating a 1/2 angular width, are defined as the morphological parameters, as shown in Fig. 14.

Fig. 14. Cone model coordinate system and transform coordinate system (Source: Xie et al. 2004).

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When the circular cross section in the apex-centered right cone coordinate system is projected onto the heliocentric coordinate system, it takes an oval shape, as shown in Fig. 15. That is, a halo CME obtained from LASCO C3 images of the heliocentric coordinate system is assumed as an oval, and using the position of the semi-major and semi-minor axes (a₁, a₂, b₁, b₂) of the cone projected from the heliocentric coordinate system, the morphological parameters (α, θ, ϕ, λ, and ω) are produced as follows (Xie et al. 2004):

Fig. 15. Cone projected onto the heliocentric coordinate system.

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$\begin{array}{l}a=0.5{\left[{\left(a_{2x}-a_{1x}\right)}^2+{\left(a_{2y}-a_{1y}\right)}^2\right]}^{1/2}\\ b=0.5{\left[{\left(b_{2x}-b_{1x}\right)}^2+{\left(b_{2y}-b_{1y}\right)}^2\right]}^{1/2}\\ \alpha ={\text{tan}}^{-1}\left(\frac{a_{2y}-a_{1y}}{a_{2x}-a_{1x}}\right),\hspace{0.17em}h={\left(a_{2x}^2+a_{2y}^2\right)}^{\frac{1}{2}}-a\\ \theta ={\text{sin}}^{-1}\left(\frac{a}{b}\right)\\ \omega ={\text{tan}}^{-1}(\frac{b}{h}\cdot \text{cos}\theta )\\ \lambda ={\text{tan}}^{-1}(\frac{\text{cos}\theta \cdot \text{sin}\alpha }{{({(\text{cos}\theta \cdot \text{sin}\alpha )}^2+{(\text{sin}\theta )}^2)}^{1/2}})\\ \varphi ={\text{tan}}^{-1}(\frac{\text{cos}\theta \cdot \text{sin}\alpha }{\text{sin}\theta })\end{array}$

In Fig. 16, based on the CME (red) extracted from an RDIFF image with the median technique applied, the CME interface (blue) was determined, and using this interface, an ellipse (green) was constructed. Using the positions of the semi-major and semi-minor axes of this ellipse, the morphological parameters are determined as α=21.74°, θ=55.51°, ϕ=32.55°, λ=12.11°, and ω=60.59°. When a CME extracted from an RDIFF image using the median technique turns out to be a halo CME, an ellipse (green) is formed, as shown in Fig. 16; otherwise, an ellipse does not appear.

Fig. 16. Example of constructing ellipse over determined halo CME (Image source: https://sohowww.nascom.nasa.gov//data/REPROCESSING/ Completed/).

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To determine if consecutively detected halo CMEs are from the same event, a matching analysis is required. For this type of analysis, the range of variation of morphological parameters (α, θ, ϕ, λ, and ω) for consecutively detected halo CMEs should be analyzed as a function of time for the same event. Thus, for 17 halo CME event periods observed during the period of 2000 to 2015, the variation in morphological parameters was analyzed, and the range of variation was determined. According to this analysis, when the variation in the position information, θ, ϕ, and λ, is limited to 20°, and the variation in 1/2 angular width, ω, is less than 40° over time, the halo CMEs should be considered to be from the same event. In addition, the lengths of semi-major and semi-minor axes should be increased over time.

When halo CMEs are found to be from the same event, 3-D characteristic factors are determined by utilizing the morphological parameters. These factors are used as an input into the ENLIL-cone model to predict the arrival time of a halo CME at Earth. The resultant 3-D parameters derived to feed into the ENLIL model are as follows:

The actual velocity of a halo CME, V_r, is generated according to the following process based on Xie et al. (2004).

Assuming that a halo CME propagates at an actual constant speed of V_r from the sun, the predicted time when the halo CME arrives at 21.5 Rs, T21.5Rs, is finally calculated as follows:

For the halo CME event at 18:23 UT on Jan. 7, 2014, the resultant images obtained from the 2013 CME analysis program are shown in Fig. 19. In Fig. 17, the CME detection results of a LASCO C3 image, SETREO A image, and STEREO B image are shown from the left. The program detected the CME, but failed to detect the halo CME; in the LASCO C3 image of Fig. 17 (left), in particular, the region in yellow, which represents the CME angular width, is narrower than the angular width of the halo CME, which can be identified visually. As a consequence, among the 3-D physical quantities generated, the angular width was determined to be incorrect. The generated 3-D physical quantities are summarized in Table 4.

Fig. 17. Resulting image of halo CME at 18:23 UT on Jan. 7, 2014 from 2013 CME analysis model (Image source: https://stereo-ssc.nascom.nasa. gov/beacon/beacon_secchi.shtml/).

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For the halo CME event at 18:23 UT on Jan. 7, 2014, the resultant images obtained through the prototype program developed in this study are shown in Fig. 18. For this event period, whereas the LASCO C3 images were obtained about ten times for every 12 min during the period of 18:54 to 20:42 UT on Jan. 7, 2014, only the resulting images at 18:54, 19:18, 19:54, and 20:42 UT are shown. The CME shapes were extracted consecutively, and by analyzing the interface of the extracted CME shapes, when the CME was determined to be a halo CME, an ellipse was constructed. Consequently, the morphological parameters produced, and the basic information of the ellipse, are summarized in Table 5. In the ellipse information in Table 5, MJ indicates the length of the semi-major axis, MN represents the length of the semi-minor axis, and R is the farthest distance from the solar center on the CME interface; all values are indicated by the size of the pixel. Using the ellipse information of morphological parameters produced, a matching analysis was conducted, and as a result, the halo CMEs were determined to be from the same event. For the halo CME identified for the period of 18:54 to 20:42 UT on Jan. 7, 2014, using the morphological parameters and ellipse information, 3-D physical quantities were finally produced, and are summarized in Table 6.

Fig. 18. Analysis result image of halo CME at 18:23 UT on Jan. 7, 2014 from prototype method (Image source: https://sohowww.nascom.nasa.gov//data/ REPROCESSING/Completed/).

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For the halo CME event at 03:38 UT on Mar. 23, 2014, the resultant images obtained from the 2013 CME analysis program are shown in Fig. 19. In Fig. 19, the CME detection results of a LASCO C3 image, SETREO A image, and STEREO B image are shown from the left. The program detected the halo CME successfully using the LASCO C3 and STEREO B images, but detected another CME using STEREO A images. Thus, incorrect 3-D physical quantities were generated, and are summarized in Table 7.

Fig. 19. Image of halo CME analysis result at 03:38 UT on Mar. 23, 2014 from CME analysis model (Image source: https://stereo-ssc.nascom.nasa. gov/beacon/beacon_secchi.shtml/).

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For the halo CME event at 03:38 UT on Mar. 23, 2014, the resultant images obtained through the prototype program developed in this study are shown in Fig. 20. For this event period, the LASCO C3 images were obtained about four times for every 12 minutes during the period of 05:18 to 05:54 UT on Mar. 23, 2014. The CME shapes were extracted consecutively, and analyzing the interface of extracted CME shapes, they turned out to be a halo CME, and an ellipse was constructed. Finally, the produced morphological parameters and the basic information of the ellipse are summarized in Table 8. Using the ellipse information of morphological parameters produced, a matching analysis was conducted, and as a result, the halo CMEs were determined to be from the same event. For the halo CME identified for the period of 05:18 to 05:54 UT on Mar. 23, 2014, using the morphological parameters and the ellipse information, 3-D physical quantities were finally produced, and are summarized in Table 9.

Fig. 20. Analysis result image of halo CME at 03:38 UT on Mar. 23, 2014 (Image source: https://sohowww.nascom.nasa.gov//data/REPROCESSING/ Completed/).

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For the halo CME event at 12:55 UT on Apr. 18, 2014, the resultant images obtained from the previous CME analysis program of 2013 are shown in Fig. 21. In Fig. 21, the results of a LASCO C3 image, SETREO A image, and STEREO B image are shown from the left. For this event period, whereas the program detected the halo CME successfully using the LASCO C3 and STEREO B images, it detected the angular width of the halo CME more narrowly than that identified visually using the STEREO A images. Thus, among the 3-D physical quantities, the angular width was proved to be incorrect. The generated 3-D physical quantities are summarized in Table 10.

Fig. 21. Analysis result of halo CME at 12:55 UT on Apr. 18, 2014 from 2013 CME analysis model (Image source: https://stereo-ssc.nascom.nasa. gov/beacon/beacon_secchi.shtml/).

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For the halo CME event at 12:55 UT on Apr. 18, 2014, the resultant images obtained through the prototype program developed in this study are shown in Fig. 22. For this event period, the LASCO C3 images were obtained about six times for every 12 minutes during the period of 13:54 to 15:06 UT on Apr. 18, 2014. Among these images, the images at 13:54, 14:06, 14:42, and 15:06 UT are shown. The CME shapes were extracted consecutively, and analyzing the interface of the extracted CME shapes, they were determined to be a halo CME, and an ellipse was constructed. Finally, the produced morphological parameters and the basic information of the ellipse are summarized in Table 10. Using the ellipse information of the morphological parameters produced, a matching analysis was conducted, and as a result, the halo CMEs were determined to be from the same event. For the halo CME identified for the period of 13:54 to 15:06 UT on Apr. 18, 2014, using the morphological parameters and the ellipse information, 3-D physical quantities were finally produced, and are summarized in Table 12.

Fig. 22. Analysis result image of halo CME at 12:55 UT on Apr. 18, 2014 (Image source: https://sohowww.nascom.nasa.gov//data/REPROCESSING/ Completed/).

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For the past three halo CME events, 3-D physical quantities were generated using both the 2013 CME analysis model program and the CAT prototype CAT. Feeding these 3-D physical quantities into the ENLIL-cone model, the arrival time of the halo CME at Earth was estimated. Table 13 shows a summary of the 3-D physical quantities of the halo CME determined by the 2013 CME analysis model program, and the arrival time at Earth determined by the ENLIL-cone model. As a result, it was estimated that all three halo CME events were unable to reach Earth.Table 11Table 12

Table 14 shows a summary of the 3-D physical quantities of a halo CME determined by the prototype program developed in this study, and the arrival time at Earth as estimated using the ENLIL-cone model when applying the 3-D physical quantities. First, the halo CME that erupted on Jan. 7, 2014, was predicted to arrive at Earth on Jan. 10, 2014, the halo CME of Mar. 23, 2014 was estimated to arrive at Earth on Mar. 25, 2014, and the halo CME of Apr. 18, 2014, was estimated to reach Earth at 16:00 UT on Apr. 20, 2014. The actual arrival times of these three halo CME events are summarized in Table 15. The prototype program developed in this study predicted the arrival time of the halo CME at Earth more accurately than the 2013 CME analysis model program using the physical quantities produced through LASCO C3 images, the availability of which is stable.