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Automatic detection of solar active regions from SOHO/MDI and SDO/HMI synoptic magnetograms

Published online by Cambridge University Press:  28 September 2023

Ruihui Wang
Affiliation:
School of Space and Environment, Beihang University, Beijing, China Key Laboratory of Space Environment monitoring and Information Processing of MIIT, Beijing, China
Jie Jiang
Affiliation:
School of Space and Environment, Beihang University, Beijing, China Key Laboratory of Space Environment monitoring and Information Processing of MIIT, Beijing, China
Yukun Luo
Affiliation:
School of Space and Environment, Beihang University, Beijing, China Key Laboratory of Space Environment monitoring and Information Processing of MIIT, Beijing, China
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Abstract

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We develop an adaptive method to automatically identify ARs from radial synoptic maps observed by SOHO/MDI and SDO/HMI, calibrate the detections between HMI and MDI data based on identified ARs flux and area and further derive a homogeneous dataset including ARs’ area and flux over the last two solar cycles. The data are compared with sunspot number, USAF/NOAA sunspot area, SMARPs and SHARPs and BARD area and flux, which show reasonable agreement. The identified ARs during the overlap period of MDI and HMI have the same areas as a whole while the AR flux based on MDI maps is about 1.36 times as large as that of HMI maps. Based on our dataset, we find strong ARs (|flux| > 1022Mx) contribute most to the difference between cycles 23 and 24 while other ARs (|flux| < 1022Mx) are similar in the two cycles in both area and flux.

Type
Poster Paper
Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of International Astronomical Union

References

Bobra, M. G., Sun, X., Hoeksema, J. T., et al. 2014, Sol Phys, 289, 3549 10.1007/s11207-014-0529-3CrossRefGoogle Scholar
Bobra, M. G., Wright, P. J., Sun, X., & Turmon, M. J. 2021, APJS, 256, 26 10.3847/1538-4365/ac1f1dCrossRefGoogle Scholar
Muñoz-Jaramillo, A., Werginz, Z. A., Vargas-Acosta, J. P., et al. 2016, in 2016 IEEE International Conference on Big Data (Big Data), 31943203Google Scholar
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