Statistics
Scientific paper
May 2004
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2004aas...204.3905l&link_type=abstract
American Astronomical Society Meeting 204, #39.05; Bulletin of the American Astronomical Society, Vol. 36, p.715
Statistics
Scientific paper
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 magnetic 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 relieved 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, with results applicable to modeling efforts by providing empirical discriminating information as to the pre-eruption state of the boundary magnetic field.
This effort is funded by contract F49620-03-C-0019 through the Air Force Office of Scientific Research.
Barnes Graham
Leka Kimberly Dawn
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