34th Solar Physics Division Meeting, June 2003
Session 16 Flares and Microflares II
Poster, Wednesday, June 18, 2003, 3:30-5:00pm, Mezzanine

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[16.16] Photospheric Magnetic Field Properties of Flaring vs. Flare-Quiet Active Regions II: A Magnetic Charge Topology Model and Statistical Results

G. Barnes, K. D. Leka (CoRA Div., NWRA), D. W. Longcope (Department of Physics, Montana State U.)

The complexity of the coronal magnetic field extrapolated from a Magnetic Charge Topology (MCT) model, is examined for pre-event signatures unique to solar energetic phenomena. Although extensive use has been made of quantities measured at the photosphere, it is important to consider the magnetic field in the corona, where (for example) the hard X-ray signatures of energy release in solar flares are observed. By quantifying the inferred coronal magnetic topology we are no longer limited to considering solely the magnetic state of the photosphere.

MCT is applied to temporally sampled photospheric magnetic data from the U. Hawai`i Imaging Vector Magnetograph, for 24 flare-event and flare-quiet epochs from seven active regions. We outline the methodology employed for automating the application of MCT to large data sets of complex active regions: partitioning the observed Bz at the photosphere, assigning a charge to each partition, and using this charge distribution to extrapolate the field in the corona. From the resulting field we compute the connectivity matrix \psiij, the location of null points and the intersection of separatrix surfaces, i.e. separator field lines. Parameters are constructed to describe, for example, the magnetic connectivities, the magnetic flux in those connections, and the number of separators.

Examining particular events results in no obvious trends in the magnitude and temporal evolution of the parameters just prior to flare events. Thus, we employ the same quantitative statistical approach outlined in Leka and Barnes [this session], i.e. applying discriminant analysis and Hotelling's T2-test, and ranking all four-variable discriminant functions as a proxy for a single all-variable discriminant function. We present those parameters which consistently appear in the best combinations, indicating that they may play an important role in defining a pre-event coronal state.

This work was performed under Air Force Office of Scientific Research contracts F49620-00-C-0004, F49620-03-C-0019 and F49620-02-C-0191.

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