Padinhatteeri, Sreejith, Higgins, Paul, Bloomfield, Shaun and Gallagher, Peter (2016) Automatic Detection of Magnetic δ in Sunspot Groups. Solar Physics, 291 (1). pp. 41-53. ISSN 0038-0938
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Abstract
Large and magnetically complex sunspot groups are known to be associated with flares. To date, the Mount Wilson scheme has been used to classify sunspot groups based on their morphological and magnetic properties. The most flare-prolific class, the δ sunspot group, is characterised by opposite-polarity umbrae within a common penumbra, separated by less than 2∘. In this article, we present a new system, called the Solar Monitor Active Region Tracker-Delta Finder (SMART-DF), which can be used to automatically detect and classify magnetic δ s in near-realtime. Using continuum images and magnetograms from the Helioseismic and Magnetic Imager (HMI) onboard NASA’s Solar Dynamics Observatory (SDO), we first estimate distances between opposite-polarity umbrae. Opposite-polarity pairs with distances of less that 2∘ are then identified, and if these pairs are found to share a common penumbra, they are identified as a magnetic δ configuration. The algorithm was compared to manual δ detections reported by the Space Weather Prediction Center (SWPC), operated by the National Oceanic and Atmospheric Administration (NOAA). SMART-DF detected 21 out of 23 active regions (ARs) that were marked as δ spots by NOAA during 2011 – 2012 (within ±60∘ longitude). SMART-DF in addition detected five ARs that were not announced as δ spots by NOAA. The near-realtime operation of SMART-DF resulted in many δ s being identified in advance of NOAA’s daily notification. SMART-DF will be integrated into SolarMonitor ( www.solarmonitor.org ) and the near-realtime information will be available to the public.
Item Type: | Article |
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Uncontrolled Keywords: | Active region, Sunspots, Mt. Wilson classification, δ -Spots |
Subjects: | F500 Astronomy |
Department: | Faculties > Engineering and Environment > Mathematics, Physics and Electrical Engineering |
Depositing User: | Becky Skoyles |
Date Deposited: | 25 Jun 2018 11:08 |
Last Modified: | 01 Aug 2021 08:06 |
URI: | http://nrl.northumbria.ac.uk/id/eprint/34671 |
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