Testing the current paradigm for space weather prediction with heliospheric imagers. Issue 6 (1st June 2017)

• Record Type: Journal Article
• Authors: Barnard, Luke A.; de Koning, Curt A.; Scott, Christopher J.; Owens, Mathew J.; Wilkinson, Julia; Davies, Jackie A.
• Is Part Of: Space weather. Volume 15:Issue 6(2017:Jun.)
• Page Start: 782
• Page End: 803
• Publication Date: 2017-06-01
• Subjects: coronal mass ejections -- heliospheric imaging -- citizen science -- forecasting; Space environment -- Periodicals; 551.509992
• DOI: 10.1002/2017SW001609
• Languages: English
• ISSNs: 1542-7390

Abstract

Abstract: Predictions of the arrival of four coronal mass ejections (CMEs) in geospace are produced through use of three CME geometric models combined with CME drag modeling, constraining these models with the available Coronagraph and Heliospheric Imager data. The efficacy of these predications is assessed by comparison with the Space Weather Prediction Center (SWPC) numerical MHD forecasts of these same events. It is found that such a prediction technique cannot outperform the standard SWPC forecast at a statistically meaningful level. We test the Harmonic Mean, Self‐Similar Expansion, and Ellipse Evolution geometric models, and find that, for these events at least, the differences between the models are smaller than the observational errors. We present a new method of characterizing CME fronts in the Heliospheric Imager field of view, utilizing the analysis of citizen scientists working with the Solar Stormwatch project, and we demonstrate that this provides a more accurate representation of the CME front than is obtained by experts analyzing elongation time maps for the studied events. Comparison of the CME kinematics estimated independently from the STEREO‐A and STEREO‐B Heliospheric Imager data reveals inconsistencies that cannot be explained within the observational errors and model assumptions. We argue that these observations imply that the assumptions of the CME geometric models are routinely invalidated and question their utility in a space weather forecasting context. These results argue for the continuing development of more advanced techniques to better exploit the Heliospheric Imager observations for space weather forecasting. Plain Language Summary: Predicting the arrival of coronal mass ejections (CMEs) in near‐Earth space is a challenging and important problem, as CMEs are the main driver of severe space weather. The Heliospheric Imager (HI) cameras provide observations of the plasma between the Sun and Earth and can be used to track the evolution of CMEs as they flow away from the Sun, toward Earth. Techniques have been developed to use the HI observations to predict the arrival of CMEs in near‐Earth space, potentially allowing the HI observations to be used in a space weather forecasting context. We assess how well these methods work for four CMEs observed by the HI cameras. We found that for these four events the techniques that use HI observations do not perform as well as the standard CME forecasting techniques used by the Space Weather Prediction Center. We try to improve the HI‐based predictions by using a citizen science approach to develop a better method of tracking the CMEs evolution. The improved CME tracking does not significantly improve the CME predictions and suggests that some of the assumptions in the HI based CME prediction techniques are poor assumptions. Key Points: J‐map analysis methods may be inappropriate for analyzing CME dynamics with Heliospheric Imagers Different CME geometric models are indistinguishable under realistic observational errors Heliospheric Imager data may be better exploited with more sophisticated techniques, such as data assimilation