Generation of a Solar Cycle of Sunspot Metadata Using the AIA Event Detection Framework - A Test of the System

The soon-to-be-launched Solar Dynamics Observatory (SDO) will generate roughly 2 TB of image data per day, far more than previous solar missions. Because of the difficulty of widely distributing this enormous volume of data and in order to maximize discovery and scientific return, a sophisticated automated metadata extraction system is being developed at Stanford University and Lockheed Martin Solar and Astrophysics Laboratory in Palo Alto, CA. A key component in this system is the Event Detection System, which will supervise the execution of a set of feature and event extraction algorithms running in parallel, in real time, on all images recorded by the four telescopes of the key imaging instrument, the Atmospheric Imaging Assembly (AIA). The system will run on a beowulf cluster of 160 processors. As a test of the new system, we will run feature extraction software developed under the European Grid of Solar Observatories (EGSO) program to extract sunspot metadata from the 12 year SOHO MDI mission archive of full disk continuum and magnetogram images and also from the TRACE high resolution image archive. Although the main goal will be to test the performance of the production line framework, the resulting database will have applications for both research and space weather prediction. We examine some of these applications and compare the databases generated with others currently available.