HR: 11:45h
AN: SP42A-06    [Abstracts]
TI: From Raw Data to Flare Predictions: A Fully Automated Technique
AU: * McAteer, R T
EM: j.mcateer@grasshopper.gsfc.nasa.gov
AF: National Reeearch Council NASA/GSFC, NASA/Goddard Space Flight Center, Solar Physics Division, COde 612.1, Greenbelt, MD 20771 United States
AU: Gallagher, P T
EM: peter.t.gallagher@ucd.ie
AF: University College Dublin, Department of Experimental Physics, University College Dublin,, Dublin, 4 Ireland
AU: Ireland, J
EM: ireland@cdso8.nascom.nasa.gov
AF: L-3 Communications GSI, NASA/Goddard Space Flight Center, Solar Physics Division, COde 612.1, Greenbelt, MD 20771 United States
AU: Young, A
EM: c.alex.young@gsfc.nasa.gov
AF: L-3 Communications GSI, NASA/Goddard Space Flight Center, Solar Physics Division, COde 612.1, Greenbelt, MD 20771 United States
AB: With the large volume of solar data which already exists, and expected in the near future with SDO, automated techniques are becoming increasingly vital. We present a fully automated active region extraction routine based on boundary extraction and region growing techniques applied to full disc MDI longitudinal magnetograms. Once extracted, any number of image processing techniques can be applied to the data leading to the possibility of automated classification. We discuss a large scale (9 years of MDI data, ~10,000 active region images) fractal survey of this data. This quantifies the meaning of magnetic complexity, relating lower threshold fractal dimension to the onset of large flares.
DE: 9810 New fields (not classifiable under other headings)
SC: Solar Physics Division - AAS [SP]
MN: 2005 Joint Assembly