Improved input to the empirical coronal mass ejection (CME) driven shock arrival model from CME cone models

Transcription

1 SPACE WEATHER, VOL. 4,, doi: /2006sw000227, 2006 Improved input to the empirical coronal mass ejection (CME) driven shock arrival model from CME cone models H. Xie, 1,2 N. Gopalswamy, 2 L. Ofman, 1,2 O. C. St. Cyr, 2 G. Michalek, 3 A. Lara, 4 and S. Yashiro 1,2 Received 7 February 2006; revised 19 May 2006; accepted 25 May 2006; published 17 October [1] We study the Sun-Earth travel time of interplanetary shocks driven by coronal mass ejections (CMEs) using empirical cone models. Three different cone models have been used to obtain the radial speeds of the CMEs, which are then used as input to the empirical shock arrival (ESA) model to obtain the Sun to Earth travel time of the shocks. We compare the predicted and observed shock transit times and find that the accuracy of the ESA model is improved by applying CME radial speeds from the cone models. There are two ways of calculating the shock travel time: using the ESA model or using the simplified ESA formula obtained by an exponential fit to the ESA model. The average mean error in the travel time with the cone model speeds is 7.8 compared to 14.6 with the sky plane speed, which amounts to an improvement of 46%. With the ESA formula, the corresponding mean errors are 9.5 and 11.7, respectively, representing an improvement of 19%. The cone models minimize projection effects and hence can be used to obtain CME radial speeds. When input to the ESA model, the large scatter in the shock travel time is reduced, thus improving CME-related space weather predictions. Citation: Xie, H., N. Gopalswamy, L. Ofman, O. C. St. Cyr, G. Michalek, A. Lara, and S. Yashiro (2006), Improved input to the empirical coronal mass ejection (CME) driven shock arrival model from CME cone models, Space Weather, 4,, doi: /2006sw Introduction [2] Interplanetary (IP) shocks detected in situ near 1 AU are indicative of the arrival of fast coronal mass ejections (CMEs) from the Sun [e.g., Burlaga et al., 1987; Manoharan et al., 2004]. CMEs expand outward into the interplanetary medium carrying plasma and magnetic field with speeds up to 3000 km s 1 [see, e.g., Gopalswamy, 2004]. Fast CMEs (with speeds greater than the ambient Alfvén speed) compress magnetic fields and solar wind plasma, producing IP shocks and enhanced magnetic field. The southward magnetic fields in the shock sheath and intrinsic fields in IP CMEs (ICMEs) or magnetic clouds (MCs) are the major cause of geomagnetic storms [e.g., Burlaga, 1987, 2002; Gosling, 1993; Cane et al., 2000; Gopalswamy et al., 1 Department of Physics, Catholic University of America, Washington, D. C., USA. 2 NASA Goddard Space Flight Center, Greenbelt, Maryland, USA. 3 Astronomical Observatory of Jagiellonian University, Cracow, Poland. 4 Instituto de Geofisica, Universidad Nacional Autónoma de México, Mexico City, Mexico. Copyright 2006 by the American Geophysical Union 2000a, 2005a; Webb et al., 2000]. Because of the strong geoeffectiveness of some halo CMEs, the prediction of the arrival of the CMEs and associated IP shocks is of crucial importance for the forecast of geomagnetic storms. [3] Gopalswamy et al. [2001] proposed an empirical CME arrival (ECA) model to predict the arrival of ICMEs on the basis of the CME speed measurements near the Sun and near 1 AU. The CME speeds used in developing this model were free from projection effects because the measuring spacecrafts were in quadrature. This kinematic model has recently been extended to the empirical shock arrival (ESA) model to predict the Earth arrival of IP shocks [Gopalswamy et al., 2005b, 2005c]. Both the ECA and ESA models require the CME s initial space speed as an input parameter. One of the difficulties in obtaining the CME initial space speed is the uncertainty due to projection effects [Gopalswamy et al., 2000b]. One cannot use a simple projection correction based on the solar source location of CMEs because CMEs may not expand uniformly during the initial phase of the CME onset [Gopalswamy et al., 2001]. The white light coronagraphs such as the Large Angle and Spectrometric Coronagraph (LASCO) onboard the Solar and Heliospheric Observatory (SOHO) provide information on CME motion as projected 1of8

2 Figure 1. Comparison of predicted halos (dark circles) at two radial distances (r = 9.5 and 15.8 R s ), superposed on observed halos at corresponding times (adapted from Figure 4 of Zhao et al. [2002]; only two frames of the figure are used). in the plane of the sky (POS). Therefore the measured speed, angular width, and the central position angle from LASCO data are all projected in POS. The real angular width, the radial speed, and the central position angle cannot be measured directly from white light LASCO images unless CMEs are ejected exactly from the solar limbs (i.e., at a right angle to the Sun-Earth line), as used by Gopalswamy et al. [2001]. [4] In white light coronagraphic images, most of the CMEs near the solar limbs are seen as cone-shaped plasma structures with an angular width that remains nearly constant in the coronagraphic field of view [e.g., Fisher and Munro, 1984; St. Cyr et al., 2000; Webb et al., 1997, 2000; Schwenn et al., 2005]. The halo CMEs, which appear as a bright cloud surrounding the occulting disk, have been interpreted as a cone-shaped plasma ejected toward (or away from) the observer on Earth [Howard et al., 1982]. Assuming that the cone geometric and kinematical characteristics hold true for halo CMEs, one can determine their propagation direction and the space speeds. In the past, the cone model has been applied to halo and partial halo CMEs by different authors [e.g., Zhao et al., 2002; Michalek et al., 2003; Xie et al., 2004] to determine the speed, size and propagating direction of CMEs. More recently, Zhao et al. (private communication, 2005; stanford.edu/zhao/zhao.html) and Xue et al. [2005] extended the cone model to an ice cream cone model by adding a spherical top to the cone. The ice cream cone models provide improved determination of the configuration of the CMEs. The improved models can also be applied to nonhalo CMEs and result in a better determination of the radial speed of CMEs which are less than 45 away from the solar limb. Zhao et al. (private communication, 2005) and Cremades and Bothmer [2005] also suggested that some CMEs may be better approximated by elliptic cones that are characterized by an elliptic cross section. [5] In this study, we consider only the first three cone models, i.e., ZPL [Zhao et al., 2002], MGY [Michalek et al., 2003], and XOL [Xie et al., 2004], apply them to a set of halo CMEs originating from near the disk center (within ±45 in latitude and longitude) to determine their radial speeds. We then use these radial speeds as input to the ESA model in order to predict the Sun-Earth travel time of the CMEdriven shocks. We estimate the accuracy of the ESA model by comparing the predicted travel times with observations. We also intercompare the results obtained from the three cone models and discuss their similarities and differences. The paper is organized as follows. Section 2 gives a brief review of the three cone models. Section 3 describes shock travel time and section 4 presents data selection and results. Discussion and conclusions are given in section CME Cone Models [6] All three CME cone models are based on the following assumptions: (1) the CME appears as halo or partial halo in the coronagraphic field of view; (2) the CMEs move out with nearly constant angular width through the corona; (3) the source locations of CMEs are in the vicinity of the solar disk center; and (4) the CME bulk velocity is along the radial direction with a uniform expansion. [7] Four free parameters are needed to define each of the cone models: the radial distance (r) from the center of the Sun, the half angular width (w) of the cone, and the angular position (latitude, l, longitude, f) of the central axis. The geometric parameters of the cone are determined using different methods in each model, as discussed below ZPL Cone Model [8] The ZPL model obtains the cone parameters by matching the observed and modeled halos for a series of radial distances (Figure 1). The model first uses test values of r, w, l, and f to fit the observed image of the CME and then adjusts the values iteratively until the best fit is obtained. Figure 1 shows an example of the fitted halo superposed on the observed halo. This halo CME appears a series of expanding bright rings centered near the disk center, which first appeared in the 2of8

3 velocities V x1 and V x2. The CME radial speed, V, half angular width of the cone, w, and the angle between the cone axis and the sky plane, q, are obtained by substituting the four measured parameters (T 1, T 2, V x1 and Figure 2. (a) Schematic illustration for the MGY model. (b) T 1, T 2, X 1, and X 2 in the LASCO C2. The thick solid arrow (X axis) denotes the direction along which V x1 and V x2 are measured. LASCO C3 field of view at 0806:05 UT. The CME radial velocity and acceleration are then obtained from the resulting (r, t) data pairs MGY Cone Model [9] As opposed to the ZPL model, where the CME originates from the center of the Sun, the MGY model sets the apex of the cone at the solar surface of the source region. MGY model measures the first appearance times (T 1, T 2 ) of halo CMEs above opposite limbs in the LASCO C2 images (see Figure 2), and the corresponding projected Figure 3. Schematic illustration for the XOL model: (a) side view containing the Sun-Earth line and (b) field of view of the LASCO C3, where (a, b, h) are semiminor radius, semimajor radius, and the distance of the ellipse from the disk center, respectively. The coordinate (x h, y h, z h ) is the heliocentric coordinate system, where z h points to Earth, y h points north, and the x h y h plane defines the plane of the sky. The cone coordinate consists of the cone axis x c and the base of the right cone. 3of8

4 Table 1. List of CME-IP Shocks and Shock Travel Times a CME Date and Time, UT V SKY, V XOL, V MGY, V ZPL, km s 1 km s 1 km s 1 km s 1 IS Date and Time, UT NA n/a NA n/a a Second and third columns are CME date/time and sky plane speed. The dates are given in the format year/month/day. Fourth through sixth columns are CME actual speeds from XOL, MGY, and ZPL models. Seventh column is IP shock arrival date and time from observations. Eighth column is shock observational shock travel times. Ninth through twelfth columns are predicted shock travel times of equation (12) using three CME cone model speeds and sky plane speed. NA means not available. T O, T XOL, T MGY, T ZPL, T SKY, V x2 ) into the following equations, derived from the geometric properties of the cone: cosð180 q wþ ¼ V x2 V ; ð4þ ð T 2 T 1 ¼ 2R þ r 0Þ ð 2R r 0Þ V x2 cosðþ¼ q r 0 R cosðq wþ ¼ V x1 V ; V x1 ð1þ ð2þ ð3þ where R denotes the solar radius XOL Cone Model [10] The XOL model is an extension of the ZPL model. Instead of using the visual image fitting method, the XOL model employs an analytical method to determine the radial speed by carrying out the coordinate transformation between the cone system and the heliocentric system of coordinates. The model is applied to a CME by determining the symmetry axis of the elliptical projection (minor axis) and the perpendicular axis (major axis) in the LASCO CME image (see Figure 3). The semimajor radius b, 4of8

5 Figure 4. Comparison of the predicted shock transit times with observations. Dotted curves show the prediction from equation (11). Dashed curves show the prediction from equation (12). Diamonds denote the observed shock travel times. semiminor radius a, and the origin O 0 (x 0, y 0 ) of the ellipse are obtained from the image. The model then calculates the angular width (w) and central axis position angle (a, q) by substituting the four measured parameters a, b, x 0,and y 0 into the following set of equations, derived from the geometric relations between the circular cone section at r and its projection: tan a ¼ y 0 x 0 a ¼ r sin w sin q b ¼ r sin w ð5þ ð6þ ð7þ qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi h ¼ r cos w cos q; h ¼ x 2 0 þ y2 0; ð8þ where h is the distance of the ellipse from the disk center, a is the angle between the cone axis projection and x h axis in the plane of the sky, and q is the angle between the cone axis and the plane of the sky. After the cone parameters (w, a, q) are determined, the radial speed is then derived from the plane of the sky speeds at specific measurement position angles. 3. Shock Travel Time [11] We obtain the observed travel time by subtracting the CME onset time from the shock onset time. The CME first appearance time in the LASCO C2 field of view is defined as the CME onset time (note that the extrapolated CME onset time at 1 R s might differ from the C2 first appearance time by several ). We then compare the observed shock travel times with the ESA model predictions [Gopalswamy et al., 2005b, 2005c]. In the ESA model, it is postulated that the CME speed changes due to the interaction with the solar wind or other CMEs resulting in an average acceleration, a, that depends linearly on the CME initial space speed, u: a = u. The CME travel time (t) is obtained from the kinematic equation: S = ut + 1 = 2 at 2, where S is the travel distance. Gopalswamy et al. [2001] also assumed that the CME acceleration ceases once the CME speed is equal to the solar wind speed. Let d 1 be the acceleration cessation distance 5of8

6 Figure 5. Histograms showing the distribution of errors (absolute values) in the travel time with equation (11) using XOL, MGY, ZPL, and sky plane CME speeds, respectively, as input. and d 2 = 1AU d 1, then the travel time t = t 1 + t 2, where t 1 and t 2 are the times taken by CMEs to travel d 1 and d 2, respectively: t 1 ¼ u þ p ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi u 2 þ 2ad 1 a d 2 ð9þ t 2 ¼ p ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi : ð10þ u 2 þ 2ad 1 [12] If the solar wind plasma is swept up faster than the local Alfvén speed, then a fast shock forms ahead of the CME at a distance DR = R sh R p (the standoff distance), where R sh and R p are the positions of the shock and the piston (CME ejecta), respectively. Using the gas dynamic approximation, the shock travel time can be determined as [Gopalswamy et al., 2005b]: t s ¼ t Dt ¼ t DR=V p ¼ t R p ððg þ 1Þ=2 1Þ=V p ; ð11þ where V p is the ICME speed, g is the ratio of specific heats, and R p is the major radius of the ICME structure, typically AU (we used R p = 0.5 AU). [13] The ESA model can be approximated by the following functional form [Gopalswamy et al., 2005c]: T ¼ ab V þ c; a ¼ 151:002; b ¼ 0:998625; c ¼ 11:5981; ð12þ where T is the shock travel time, V is the average speed of the CME near the Sun within the coronagraphic field of view, and (a, b, c) are coefficients of the exponential fit to the predicted results [Gopalswamy et al., 2005c]. Note that equation (12) is valid only for V > 500 km s Data and Results [14] Table 1 lists 40 CME-IP shock events. We chose the frontside halo CMEs listed by Michalek et al. [2004] with CME brightness quality >1.0 from 1997 to 2002 plus two extreme events from the Halloween storm in 2003 [Gopalswamy et al., 2005c]. Only those halo CMEs originating within ±45 from the center of the Sun have been selected. The first column is the number of the events. The second and third columns list the CME C2 first appearance date/time and the sky plane speed obtained from the LASCO CME catalog ( CME_list) [Yashiro et al., 2004]. The fourth through sixth columns are the CME radial speeds computed using the three cone models. The seventh column lists the observed IP shock onset date and time obtained from the Wind spacecraft observations (available at wind/current_listips.htm). The eighth column presents the observed shock travel time, computed as the difference between the CME onset time and IP shock onset time. The ninth through twelfth columns are the predicted shock travel times using the three cone model speeds and the sky plane speed as input to equation (12). The shock onset times were cross checked with published lists of Manoharan et al. [2004] and Gopalswamy et al. [2005b] and the last two events in Table 1 are from Gopalswamy et al. [2005c]. [15] The shock travel times versus CME velocities are shown in Figure 4, which compares the observed values Figure 6. Histograms showing the distribution of the errors (absolute values) in the travel time with equation (12) using XOL, MGY, ZPL, and sky plane CME speeds, respectively, as input. 6of8

7 Table 2. Improvement in the Mean Error by the Cone Models a Mean Error_ XOL, Mean Error_MGY, Mean Error_ZPL, Mean Error_SKY, AVG_three, AVG_XOL&ZPL, AVG_three Improvement, % AVG_XOL&ZPL Improvement, % Equation (11) Equation (12) a Sixth column is the average mean error of the three cone models. Seventh column is the average mean error of the XOL and ZPL model. The percentage of the improvement in the mean error is computed as (AVG -- Mean_error_SKY)/Mean_error_SKY, where AVG denotes the average mean error of the cone models. (diamond symbols) for the 40 shocks with the ESA model predictions. Figures 4a-- 4d present four cases using the XOL, MGY, ZPL radial speeds, and the sky plane speed, respectively, as the initial CME speed. As we can see from Figure 4, the observed shock travel times agree quite well with the ESA model curves, although the values obtained from equation (12) are slightly larger than those from equation (11). In Figures 4a--4c, the scatter of the data points relative to the ESA model curves is smaller than that in Figure 4d, implying that the accuracy of the ESA model improves when the radial speeds (rather than the sky plane speed) are used as input. [16] Figures 5 and 6 show the distribution of errors (absolute values) obtained as the difference between the predicted and observed shock travel times for the above four cases. The mean errors in Figure 5 are 7.9, 9.1, 6.3 and 14.6, respectively. The average of the errors with input from the three cone models is 7.8 and the improvement in the mean error is 46% (6.8/14.6) with respect to the sky plane speed input. The mean errors in Figure 6 are 6.5, 12.8, 9.2 and 11.7, respectively. The average of the errors with input from the three cone models is 9.5 and the improvement in the mean error is 19% (2.2/11.7). Table 2 lists the percentages of improvement in the mean error along with the original error values. 5. Discussion and Conclusions [17] In this paper, we have compared the ESA model shock travel times using CME speed input from three different cone models. When sky plane speeds are used, the ESA model provides a reasonable prediction and agrees well with observations for medium-speed CME events ( km s 1 ), but the prediction of the ESA model is relatively poor for some slow (<700 km s 1 ) and fast (>1300 km s 1 ) CME events. The accuracy of the ESA model is improved significantly when the CME radial speeds are used. The mean errors in the travel time from the XOL, MGY, and ZPL models are 7.9 (6.5), 9.1 (12.8), and 6.3 (9.2) using equations (11) and (12), respectively; compared to the sky plane speed mean error of 14.6 (11.7), the average mean error of the three cone models is 7.8 (9.5), amounting to an improvement of 46% (19%). When one excludes the MGY model, the average mean error of XOL and ZPL is 7.1 (7.85), representing an improvement of 51% (33%). The XOL and ZPL models show a better improvement over the sky plane speed compared to the MGY model. Among the three cone models, the XOL model provides the best results with equation (12) and the ZPL model provides the best results with equation (11). [18] Cane and Richardson [2003] stated that an empirical formula such as the ECA model for ejecta transit time based on CME speed is not particularly reliable because of the large scatter in ejecta arrival times for similar CME speeds. However, their argument was based on using CME projected speeds. Because of projection effects, similar sky plane speeds may correspond to different CME space speeds (depending on the variation of the projection angle), thus resulting in different ejecta arrival times (and hence the scatter in arrival times). Furthermore, the ECA and ESA models were originally developed using CME measurements free from projection effects [Gopalswamy et al., 2001], where a set of limb CMEs (without projection effects) observed by Solwind Coronagraph and Helios 1 have been used to deduce the accelerations of CMEs. They are only appropriate to use CME radial speeds, not the sky plane speeds as input. The present work has demonstrated that when the CME radial speed is used in the ESA model the scatter is reduced significantly and improves the travel time prediction. Note that the sky plane speed is measuring the motion of the CME central leading edge (or ice cream cone apex), which is generally greater that the flank shock speed. When CMEs are propagating at angle (90 q) away from the line of sight, we estimate the shock speed by choosing the measurement position angle of the CME cone part (opposed to the ice cream cone apex), which is the Earth-directed component. In this study, we managed to correct for both lower and higher apparent speeds from projection effects using cone models, thus the mean error of the ESA model has been significantly reduced, enabling better space weather predictions. [19] Acknowledgments. The authors would like to thank the support of Wind and Advanced Composition Explorer (ACE) teams and National Space Science Data Center (NSSDC) center for processing data. This work was supported by NASA LWS and the NSF Solar, Heliospheric, and Interplanetary Environment (SHINE ATM ) program. H.X. and L.O. are supported by NSF grant ATM of8

8 References Burlaga, L. F., K. W. Behannon, and L. W. Klein (1987), Compound streams, magnetic clouds, and major geomagnetic storms, J. Geophys. Res., 92, Burlaga, L. F., S. P. Plunkett, and O. C. St. Cyr (2002), Successive CMEs and complex ejecta, J. Geophys. Res., 107(A10), 1266, doi: /2001ja Cane, H. V., and I. G. Richardson (2003), Reply to comment on Coronal mass ejections, interplanetary ejecta and geomagnetic storms by Gopalswamy et al., Geophys. Res. Lett., 30(24), 2233, doi: /2003gl Cane, H. V., I. G. Richardson, and O. C. St. Cyr (2000), Coronal mass ejections, interplanetary ejecta and geomagnetic storms, Geophys. Res. Lett., 27, Cremades, H., and V. Bothmer (2005), Geometrical properties of coronal mass ejections, in IAU Symposium Proceedings of the International Astronomical Union 226, edited by K. Dere, J. Wang, and Y. Yan, p. 48, Cambridge Univ. Press, New York. Fisher, R. R., and R. H. Munro (1984), Coronal transient geometry. I The flare-associated event of 1981 March 25, Astrophys. J., 280, 428. Gopalswamy, N. (2004), A global picture of CMEs in the inner heliosphere, in The Sun and the Heliosphere as an Integrated System, ASSL Ser., vol. 317, edited by G. Poletto and S. Suess, chap. 8, p. 201, Springer, New York. Gopalswamy, N., A. Lara, R. P. Lepping, M. L. Kaiser, D. Berdichevsky, and O. C. St. Cyr (2000a), Interplanetary acceleration of coronal mass ejections, Geophys. Res. Lett., 27, 145. Gopalswamy, N., M. L. Kaiser, B. J. Thompson, L. F. Burlaga, A. Szabo, A. Lara, A. Vourlidas, S. Yashiro, and J.-L. Bougeret (2000b), Radiorich solar eruptive events, Geophys. Res. Lett., 27, Gopalswamy, N., A. Lara, S. Yashiro, M. L. Kaiser, and R. A. Howard (2001), Predicting the 1-AU arrival times of coronal mass ejections, J. Geophys. Res., 106, 29,207. Gopalswamy, N., S. Yashiro, G. Michalek, H. Xie, R. P. Lepping, and R. A. Howard (2005a), Solar source of the largest geomagnetic storm of cycle 23, Geophys. Res. Lett., 32, L12S09, doi: / 2004GL Gopalswamy, N., A. Lara, P. K. Manoharan, and R. A. Howard (2005b), An empirical model to predict the 1-AU arrival of interplanetary shocks, Adv. Space Res., 36, Gopalswamy, N., S. Yashiro, Y. Liu, G. Michalek, A. Vourlidas, M. L. Kaiser, and R. A. Howard (2005c), Coronal mass ejections and other extreme characteristics of the October-- November solar eruptions, J. Geophys. Res., 110, A09S15, doi: /2004ja Gosling, J. T. (1993), Coronal mass ejections---the link between solar and geomagnetic activity, Phys. Fluids B, 5, Howard, R. A., D. J. Michels, N. R. Sheeley Jr., and M.J. Koomen (1982), The observation of a coronal transient directed at Earth, Astrophys. J., 263, L101. Manoharan, P. K., N. Gopalswamy, S. Yashiro, A. Lara, G. Michalek, and R. A. Howard (2004), Influence of coronal mass ejection interaction on propagation of interplanetary shocks, J. Geophys. Res., 109, A06109, doi: /2003ja Michalek, G., N. Gopalswamy, and S. Yashiro (2003), A new method for estimating widths, velocities, and source location of halo coronal mass ejections, Astrophys. J., 584, 472. Michalek, G., N. Gopalswamy, A. Lara, and P. K. Manoharan (2004), Arrival time of halo coronal mass ejections in the vicinity of the Earth, Astron. Astrophys., 423, 729. Schwenn, R., et al. (2005), The association of coronal mass ejections with their effects near the Earth, Ann. Geophys., 23, St.Cyr,O.C.,etal.(2000),Propertiesofcoronalmassejections: SOHO LASCO observations from January 1996 to June 1998, J. Geophys. Res., 105, 18,169. Webb, D. F., S. W. Kahler, P. S. McIntosh, and J. A. Klimchuk (1997), Large-scale structures and multiple neutral lines associated with coronal mass ejections, J. Geophys. Res., 102, 24,161. Webb, D. F., E. W. Cliver, N. U. Crooker, O. C. St. Cyr, and B. J. Thompson (2000), Relationship of halo coronal mass ejections, magnetic clouds, and magnetic storms, J. Geophys. Res., 105, Xie, H., L. Ofman, and G. Lawrence (2004), Cone model for halo CMEs: Application to space weather forecasting, J. Geophys. Res., 109, A03109, doi: /2003ja Xue, X. H., C. B. Wang, and X. K. Dou (2005), An ice-cream cone model for coronal mass ejections, J. Geophys. Res., 110, A08103, doi: /2004ja Yashiro, S., N. Gopalswamy, G. Michalek, O. C. St. Cyr, S. P. Plunkett, N. B. Rich, and R. A. Howard (2004), A catalog of white light coronal mass ejections observed by the SOHO spacecraft, J. Geophys. Res., 109, A07105, doi: /2003ja Zhao, X. P., S. P. Plunkett, and W. Liu (2002), Determination of geometrical and kinematical properties of halo coronal mass ejections using the cone model, J. Geophys. Res., 107(A8), 1223, doi: / 2001JA N. Gopalswamy, L. Ofman, O. C. St. Cyr, H. Xie, and S. Yashiro, NASA GSFC, Greenbelt, MD 20771, USA. (hong.xie@ssedmail.gsfc. nasa.gov) A. Lara, Instituto de Geofisica, UNAM, Mexico DF 04510, Mexico. G. Michalek, Astronomical Observatory of Jagiellonian University, Orla 171, Cracow, Malopolska , Poland. 8of8