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Solar thematic maps for space weather operations

Space Weather

By:
, , , and
DOI: 10.1029/2012SW000780

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Abstract

Thematic maps are arrays of labels, or "themes", associated with discrete locations in space and time. Borrowing heavily from the terrestrial remote sensing discipline, a numerical technique based on Bayes' theorem captures operational expertise in the form of trained theme statistics, then uses this to automatically assign labels to solar image pixels. Ultimately, regular thematic maps of the solar corona will be generated from high-cadence, high-resolution SUVI images, the solar ultraviolet imager slated to fly on NOAA's next-generation GOES-R series of satellites starting ~2016. These thematic maps will not only provide quicker, more consistent synoptic views of the sun for space weather forecasters, but digital thematic pixel masks (e.g., coronal hole, active region, flare, etc.), necessary for a new generation of operational solar data products, will be generated. This paper presents the mathematical underpinnings of our thematic mapper, as well as some practical algorithmic considerations. Then, using images from the Solar Dynamics Observatory (SDO) Advanced Imaging Array (AIA) as test data, it presents results from validation experiments designed to ascertain the robustness of the technique with respect to differing expert opinions and changing solar conditions.

Additional Publication Details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
Solar thematic maps for space weather operations
Series title:
Space Weather
DOI:
10.1029/2012SW000780
Volume
10
Year Published:
2012
Language:
English
Publisher:
American Geophysical Union
Contributing office(s):
Geologic Hazards Science Center
Description:
S08009, 16 p.
Larger Work Type:
Article
Larger Work Subtype:
Journal Article
Larger Work Title:
Space Weather
Country:
United States