A live homogeneous database of solar active regions based on SOHO/MDI and SDO/HMI synoptic magnetograms

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Wang, Ruihui

IAU S365

Wang, R.-H., Jiang, J., Luo, Y.-K., 2023, accepted by ApJS

https://arxiv.org/abs/2308.06914

《穿越太阳》任务设计

Key points

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• We develop an AR database for understanding and predicting the solar cycle.
• Time range: cycles 23, 24, and part of cycle 25
• Basic parameters: area, flux, etc.
• New parameters quantifying the contribution of an AR to the solar cycle: final dipole field (or moment) (FDF), degree of rogueness (DOR), etc.

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• Although cycles 24 is significantly weaker than cycle 23 based on the sunspot number, weak (small) AR parameters, including number, area, and flux, show a very weak dependence of cycle strength.

Final dipole field (FDF)

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• Active regions (ARs) account for the generation of the Sun’s poloidal field (Babcock 1961; Leighton 1969).

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• The magnetic field of ARs 🡪 the polar field.

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• Final dipole field (FDF) measures the contribution of an AR to the end-of-cycle polar field.

Evolution of an AR’s magnetic field (Jiang et al. 2019).

Degree of Rogueness (DOR)

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• Although the emergence of ARs shows systematic properties in their latitude and tilt angle (Jiang et al. 2011), there are also strong stochastic components, Such as anti-Hale AR, anti-Joy AR, especially ARs with various configuration.
• Degree of Rogueness (DOR) (Nagy et al. 2020) describes the stochasticity.
• DOR is important for the solar cycle prediction.

An AR database that offers FDF and DOR would be valuable for understanding and predicting the solar cycle.

ARs with various configurations

AR detection method and results

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• excludes decayed ARs and unipolar regions
• compatible with available synoptic magnetograms

Detection method: morphological operations and region growing (Wang et al. 2023)

Examples of results:

Advantages:

Comparison with other detections

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MDI CR 2000

• Our detections are similar to Zhang et al. (2010) & NOAA in general.
• There are several unipolar regions in both Zhang et al. (2010) and NOAA.
• Our detections are more complete for ARs No. 3, 5 and 12.

Zhang et al. (2010)

Zhang et al. (2010) : black square

NOAA : red circle

Comparison with other databases

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Our database shows similar trend of the time evolution of AR number, area, and unsigned flux in two cycles with other databases.

WYM: Whitbread et al. (2018)

FDF calculation

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Wang et al. (2021): proposed a generalized method, which is equivalent to the surface flux transport model and provide a quick and precise quantification of an AR contribution to solar cycle evolution.

• dd

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observation

DOR calculation

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• DOR describes the deviation of the dipole contribution from the case with reduced stochastic perturbations in AR emergence (Petrovay et al. 2020)
• Reduced stochastic perturbations: simplify an AR to a BMR which obey Joy’s law, Hale’s law, and correlation between the polarity separation and flux

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DOR: result

The distribution of DORs.

The DORs at the two end are all DORs bigger than the thresholds.

Overview of Our AR Database

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• 15 parameters:

CR number, label, latitude, longitude, area, flux

Initial dipole field, final dipole field, and DOR

(IDF, FDF, and DOR will be given in the website soon.)

• Time range:

Now：May 5th, 1996, to June 14th, 2023 (CRs 1909 - 2271)，will be extended continuously

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• Number:

Total：2575 ARs ；

Cycle 23：1399 ；Cycle 24： 1176

• Detection method and database ：

https://github.com/Wang-Ruihui/A-live-homogeneous-database-of-solar-active-regions

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Cycle variation of ARs with different strength

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For cycles 23 and 24:

• For strong ARs, the peak values of three parameters are different.
• For medium and weak ARs, the peak values of three parameters are similar.

The strength of number, area, and flux for weak ARs is weakly dependent on the cycle strength.

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THANKS！

https://github.com/Wang-Ruihui/A-live-homogeneous-database-of-solar-active-regions

wangruihui@buaa.edu.cn

Method

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Example: CR1968

5 modules: b-f

• Module1 (b) adaptive intensity threshold segmentation
• Module2 (c) closing operation and an opening operation
• Module3 (d) Region growing
• Module4 (e) eliminate small decayed AR segments
• Module5 (f) neighbor regions merging and unipolar regions removal

morphological operations region growing

Get all possible ARs

Get the whole two polarities of ARs

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Calibration of results

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CRs 2097-2107

ARs detected by both MDI and HMI

Results after calibration

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• The AR numbers are different：decayed ARs
• The AR area and flux are similar.

• Remove repeated ARs

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Repeat ARs

Flux threshold of ARs with different stength

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CR 1984-1986

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CR 1993，No.6 0.495

• Examples of Rogue ARs