Theoretical basis for operational ensemble forecasting of coronal mass ejections. Issue 10 (20th October 2015) - Pizzo, V. J.; de Koning, C.; Cash, M.; Millward, G.; Biesecker, D. A.; Puga, L.; Codrescu, M.; Odstrcil, D.
Abstract: We lay out the theoretical underpinnings for the application of the Wang‐Sheeley‐Arge‐Enlil modeling system to ensemble forecasting of coronal mass ejections (CMEs) in an operational environment. In such models, there is no magnetic cloud component, so our results pertain only to CME front properties, such as transit time to Earth. Within this framework, we find no evidence that the propagation is chaotic, and therefore, CME forecasting calls for different tactics than employed for terrestrial weather or hurricane forecasting. We explore a broad range of CME cone inputs and ambient states to flesh out differing CME evolutionary behavior in the various dynamical domains (e.g., large, fast CMEs launched into a slow ambient, and the converse; plus numerous permutations in between). CME propagation in both uniform and highly structured ambient flows is considered to assess how much the solar wind background affects the CME front properties at 1 AU. Graphical and analytic tools pertinent to an ensemble approach are developed to enable uncertainties in forecasting CME impact at Earth to be realistically estimated. We discuss how uncertainties in CME pointing relative to the Sun‐Earth line affects the reliability of a forecast and how glancing blows become an issue for CME off‐points greater than about the half width of the estimated input CME. While the basic results appear consistent with established impressions of CME behavior, the next step is to use existing records of well‐observed CMEs at both Sun and Earth to verify that real events appear to follow the systematic tendencies presented in this study. Key Points: Develop ensemble CME forecast system and pertinent analytic and graphical tools Nonchaotic propagation implies different tactics than for terrestrial weather Establishes solid theoretical basis for forecast and analysis of real events