ElEvoHI: A NOVEL CME PREDICTION TOOL FOR HELIOSPHERIC IMAGING COMBINING AN ELLIPTICAL FRONT WITH DRAG-BASED MODEL FITTING

Abstract

In this study, we present a new method for forecasting arrival times and speeds of coronal mass ejections (CMEs) at any location in the inner heliosphere. This new approach enables the adoption of a highly flexible geometrical shape for the CME front with an adjustable CME angular width and an adjustable radius of curvature of its leading edge, i.e. the assumed geometry is elliptical. Using, as input, STEREO heliospheric imager (HI) observations, a new elliptic conversion (ElCon) method is introduced and combined with the use of drag-based model (DBM) fitting to quantify the deceleration or acceleration experienced by CMEs during propagation. The result is then used as input for the Ellipse Evolution Model (ElEvo). Together, ElCon, DBM fitting, and ElEvo form the novel ElEvoHI forecasting utility. To demonstrate the applicability of ElEvoHI, we forecast the arrival times and speeds of 21 CMEs remotely observed from STEREO/HI and compare them to in situ arrival times and speeds at 1 AU. Compared to the commonly used STEREO/HI fitting techniques (Fixed-φ, Harmonic Mean, and Self-similar Expansion fitting), ElEvoHI improves the arrival time forecast by about 2 hours to ±6.5 hours and the arrival speed forecast by ≈ 250 km s −1 to ±53 km s −1 , depending on the ellipse aspect ratio assumed. In particular, the remarkable improvement of the arrival speed prediction is potentially beneficial for predicting geomagnetic storm strength at Earth. ing coronagraph observations, leads to errors in CME arrival time predictions at Earth that lie in the range of ±12 to ±18 hrs (e.g. Mays et al. 2015; Vršnak et al. 2014). Note that for a selected sample of CMEs Millward et al. (2013) obtained errors of ±7.5 hrs. The reasons for these large forecasting errors are diverse. Firstly, the observations are limited. Currently, only the LASCO C2 and C3 coronagraphs (Brueckner et al. 1995) onboard the SOlar and Heliospheric Observatory (SOHO) and the COR1 and COR2 coronagraphs onboard the Ahead spacecraft of the twin satellite mission Solar Terrestrial Relations Observatory (STEREO; Kaiser et al. 2008) can be used to operationally forecast the arrival times of Earth-directed CMEs. Secondly, the structures, shapes, orientations, sizes, directions and speeds of CMEs are highly variable, i.e. it is quite diffi-arXiv:1605.00510v2 [astro-ph.SR]

Testing the current paradigm for space weather prediction with heliospheric imagers

“…Such techniques can be applied to CMEs observed from a single spacecraft or to simultaneous observations from two spacecraft with distinct viewpoints [Lugaz, 2010;Liu et al, 2010Liu et al, , 2013. Most recently, the SSE model has been extended further to consider the CME front as elliptical rather than circular, introducing the ellipse aspect ratio as an additional free parameter, resulting in the ElCon model [Rollett et al, 2016].…”

“…These techniques include point P (PP), fixed phi (FP), harmonic mean (HM), self-similar expansion (SSE), and Ellipse Evolution (ElCon) [Howard et al, 2006;Kahler and Webb, 2007;Sheeley et al, 1999;Rouillard et al, 2008;Lugaz et al, 2009;Davies et al, 2012;Möstl and Davies, 2013;Rollett et al, 2016]. Each makes different assumptions about the geometry of a CME, but all are effectively methods to estimate the radial distance of the CME apex from the observed elongation of the CME in the HI FOV.…”

“…Setting this parameter to zero replicates the FP geometry while setting it to 90 ∘ replicates the HM geometry; intermediate values approximate the CME cross section as a self-similar expanding circle of constant half width (as discussed by Davies et al [2012]). As a result, some studies have set the half width to a value that represents a compromise between the two extremes; Möstl et al [2014] used 45 ∘ , Rollett et al [2016] used 35 ∘ , while Barnard et al [2015a] and Mishra et al [2014] used 30 ∘ . Such techniques can be applied to CMEs observed from a single spacecraft or to simultaneous observations from two spacecraft with distinct viewpoints [Lugaz, 2010;Liu et al, 2010Liu et al, , 2013.…”

A probabilistic approach to the drag-based model

“…Or, the difference can be in the way the drag effect is approximated and the velocity of the CME evolves as in Hess and Zhang (2015), Žic et al (2015) and Rollett et al (2016).…”

“…The difference may arise from the peculiarity of the data used (type and source) and from the interpretation of such data to estimate the CME onset parameters, which ultimately depends on the shape assumed for the CME itself (the Fixed-method in Sheeley et al (1999); Rouillard et al (2008); Möstl et al (2014), the Harmonic mean method in Howard and Tappin (2009);Lugaz et al (2009), the Self Similar Expansion method in Davies et al (2012); Möstl and Davies (2013), the graduated cylindrical shell method (GCS) in Thernisien et al (2006Thernisien et al ( , 2009, the Elliptic Conversion method in Rollett et al (2016), to cite the most used). Or, the difference can be in the way the drag effect is approximated and the velocity of the CME evolves as in Hess and Zhang (2015), Žic et al (2015) and Rollett et al (2016).…”