Accurate and Timely Forecasting of CME-Driven Geomagnetic Storms

Abstract:

Wide-spread and severe geomagnetic storms are primarily caused by the
ejecta of coronal mass ejections (CMEs) that impose long durations of
strong southward interplanetary magnetic field (IMF) on the
magnetosphere, the duration and magnitude of the southward IMF ($B_s$)
being the main determinants of geoeffectiveness. Another important
quantity to forecast is the arrival time of the expected geoeffective
CME ejecta. In order to accurately forecast these quantities in a
timely manner (say, 24--48 hours of advance warning time), it is
necessary to calculate the evolving CME ejecta---its structure and
magnetic field vector in three dimensions---using remote sensing solar
data alone. We discuss a method based on the validated erupting flux
rope (EFR) model of CME dynamics. It has been shown using STEREO data
that the model can calculate the correct size, magnetic field, and the
plasma parameters of a CME ejecta detected at 1 AU, using the observed
CME position-time data alone as input (Kunkel and Chen 2010). One
disparity is in the arrival time, which is attributed to the
simplified geometry of circular toroidal axis of the CME flux rope.
Accordingly, the model has been extended to self-consistently include
the transverse expansion of the flux rope (Kunkel 2012; Kunkel and
Chen 2015). We show that the extended formulation provides a better
prediction of arrival time even if the CME apex does not propagate
directly toward the earth. We apply the new method to a number of CME
events and compare predicted flux ropes at 1 AU to the observed ejecta
structures inferred from in situ magnetic and plasma data. The EFR
model also predicts the asymptotic ambient solar wind speed ($V_{sw}$) for
each event, which has not been validated yet. The predicted Vsw
values are tested using the ENLIL model. We discuss the minimum and
sufficient required input data for an operational forecasting system
for predicting the drivers of large geomagnetic storms.

Kunkel, V., and Chen, J., ApJ Lett, 715, L80, 2010.

Kunkel, V., PhD thesis, George Mason University, 2012.

Kunkel, V., and Chen, J., ApJ, submitted, 2015.

Work supported by the Naval Research Laboratory Base Research Program