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Classification of Sunspot Groups Using SOHO/MDI Magnetogram and White-Light Images

Tuesday, November 3, 2009


Background/Motivation
· Sunspot classification is (for the most part) done manually by experts in the field. · This process consumes both labor and time, and there is not always agreement on the resulting classification of particular sunspot groups. · As a result, an automatic (hence objective) and accurate procedure for classifying sunspot groups is highly desirable.

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The Data (or, what I currently have available)
· 1038 white-light images from May 19, 1996 through December 31, 1999. · 19, 347 magnetograms from 1996 through 2004.
­ ­ ­ ­ ­ ­ ­ ­ ­ 2 7 1 2 3 3 3 2 8 0 7 2 6 9 7 6 2 8 3 2 0 6 1 8 5 6 3 magnetograms from 1 magnetograms from 1 4 magnetograms from 8 magnetograms from 4 magnetograms from 1 magnetograms from 9 magnetograms from 3 magnetograms from magnetograms from 2 9 9 1 1 2 2 2 2 0 9 9 9 9 0 0 0 0 0 6 7 9 9 0 0 0 0 4 8 9 0 1 2 3

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Four types of sunspot groups

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Alpha: A unipolar sunspot group

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Beta: A sunspot group having both positive and negative magnetic polarities (bipolar), with a simple and distinct division between the polarities.
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Beta-Gamma: A sunspot group that is bipolar but which is suficiently complex that no single, continuous line can be drawn between spots of opposite polarities.
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Beta-Gamma-Delta: A sunspot group where spots of opposite polarities are scattered around the whole image.
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The Plan
An automatic sunspot detection and classification procedure will be developed using SOHO/MDI magnetogram and whitelight images.

SOHO/MDI white-light image (left) and magnetogram (right) for October 12, 1999
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White-light extraction
· In order to compare white-light images to magnetograms, we must extract data from the white-light images that corresponds (in time and 2-dimensional space) to the magnetograms we have available. To do this for each magnetogram we must: 1) Find the white-light image with the closest time signature to the magnetogram. 2) Rotate the white-light image (correcting for the diferential rotation of the sun) so that it matches the time the magnetogram was created. 3) Extract a region from the white-light image that matches the 2-dimensinal region of the magnetogram (in units of arcsecs).

·

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Example

White-light image and magnetogram for October 12, 1999
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We rotate the white-light image so that it matches the time on the magnetogram

White light image from 12-Oct-1999 11:11:33.087 UT (left) rotated to 12-Oct-199 12:51:03.090 UT (right).
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Then, we cut out a region on the white-light image that matches the magnetogram.

Magnetogram from 12-Oct-1999 12:51:03.090 UT (left) and extracted white light image from 12-Oct-1999 11:11:33.087 UT (right) diferentially rotated.

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A possible concern...
· There are some (though not many) gaps in the white-light images of up to 4 days. · Although it is possible to rotate a white light image to match the date on a magnetogram with several days diference, sunspots can evolve in a shorter period of time and the white-light image may no longer be useful.

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Magnetogram 13-Oct

12-Oct

14-Oct 16-Oct Tuesday, November 3, 2009

15-Oct


Another concern...
· Some magnetograms (particularly those taken near the edge of the solar disk) do not appear to be

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Next Steps
· Decide how to handle bad magnetograms and gaps in white light data. · Finish the automation of the white-light extraction routine. · Generate the white-light extractions to be used for classification · And then...?

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Group Discussion
· Questions/comments? · How big of a data set do we need? · What will happen once the white-light extraction data set is created? · If we want a "truly" automated system, what would be the inputs? · New/more natural classification scheme ? · Use sunspot classifications to predict solar flares?
Tuesday, November 3, 2009