Authors: K.D. Leka, Graham Barnes
Affiliation: NorthWest Research Associates, Colorado Research Associates Division
Solar active regions are often evaluated for their potential to produce energetic
events based their magnetic morphology. Quantitatively this information is available
using vector magnetic field information which is (presently only) routinely
gathered from photospheric observations. Recently we demonstrated a method of
parameterizing vector field information such that variations in the magnetic
morphology and complexity were contained in the statistical description of (as
examples) the vertical current or shear angles; it was also demonstrated that
no single parameter consistently and uniquely displayed pre-event variations
(Leka & Barnes 2003a). We also showed that with Discriminant Analysis (Leka
& Barnes 2003b), it is possible to distinguish between an event-imminent
photospheric magnetic state and an event-quiet state -- but only by considering
multiple variables simultaneously. The limitations of that demonstration were
primarily due to small-number statistics given the dataset used.
In the present work, Discriminant Analysis is applied to a very different dataset:
the daily "survey" magnetograms obtained by the U. Hawai`i/Mees Solar
Observatory Imaging Vector Magnetograph. In this manner, the problem of small-number
statistics is mitigated and advantages available by DA are explored. However,
given the daily temporal cadence the focus shifts toward detecting parametric
thresholds rather than pre-event specific evolution. Nonetheless, the central
question remains how to distinguish a region which is primed for an energetic
event, applicable to modeling efforts by providing empirical discriminating
information as to the pre-eruption state of the boundary magnetic field.
This effort is funded through contract F49620-03-C-0019 through the Air Force
Office of Scientific Research.