scholarly journals Towards an algebraic method of solar cycle prediction

2020 ◽  
Vol 10 ◽  
pp. 46 ◽  
Author(s):  
Melinda Nagy ◽  
Kristóf Petrovay ◽  
Alexandre Lemerle ◽  
Paul Charbonneau
Keyword(s):  
Dipole Moment ◽  
Solar Cycle ◽  
Active Region ◽  
Input Data ◽  
Active Regions ◽  
Algebraic Method ◽  
Dynamo Model ◽  
Good Reproduction ◽  
Detailed Statistical Analysis ◽  
Activity Cycles

An algebraic method for the reconstruction and potentially prediction of the solar dipole moment value at sunspot minimum (known to be a good predictor of the amplitude of the next solar cycle) was suggested in the first paper in this series. The method sums up the ultimate dipole moment contributions of individual active regions in a solar cycle: for this, detailed and reliable input data would in principle be needed for thousands of active regions in a solar cycle. To reduce the need for detailed input data, here we propose a new active region descriptor called ARDoR (Active Region Degree of Rogueness). In a detailed statistical analysis of a large number of activity cycles simulated with the 2 × 2D dynamo model we demonstrate that ranking active regions by decreasing ARDoR, for a good reproduction of the solar dipole moment at the end of the cycle it is sufficient to consider the top N regions on this list explicitly, where N is a relatively low number, while for the other regions the ARDoR value may be set to zero. For example, with N = 5 the fraction of cycles where the dipole moment is reproduced with an error exceeding ±30% is only 12%, significantly reduced with respect to the case N = 0, i.e. ARDoR set to zero for all active regions, where this fraction is 26%. This indicates that stochastic effects on the intercycle variations of solar activity are dominated by the effect of a low number of large “rogue” active regions, rather than the combined effect of numerous small ARs. The method has a potential for future use in solar cycle prediction.

scholarly journals Towards an algebraic method of solar cycle prediction

2020 ◽  
Vol 10 ◽  
pp. 50 ◽  
Author(s):  
Kristóf Petrovay ◽  
Melinda Nagy ◽  
Anthony R. Yeates
Keyword(s):  
Dipole Moment ◽  
Solar Cycle ◽  
Active Regions ◽  
Surface Flux ◽  
Algebraic Method ◽  
Meridional Flow ◽  
Activity Level ◽  
Dynamo Model ◽  
Flux Transport ◽  
Axial Dipole

We discuss the potential use of an algebraic method to compute the value of the solar axial dipole moment at solar minimum, widely considered to be the most reliable precursor of the activity level in the next solar cycle. The method consists of summing up the ultimate contributions of individual active regions to the solar axial dipole moment at the end of the cycle. A potential limitation of the approach is its dependence on the underlying surface flux transport (SFT) model details. We demonstrate by both analytical and numerical methods that the factor relating the initial and ultimate dipole moment contributions of an active region displays a Gaussian dependence on latitude with parameters that only depend on details of the SFT model through the parameter η/Δu where η is supergranular diffusivity and Δu is the divergence of the meridional flow on the equator. In a comparison with cycles simulated in the 2 × 2D dynamo model we further demonstrate that the inaccuracies associated with the algebraic method are minor and the method may be able to reproduce the dipole moment values in a large majority of cycles.

scholarly journals The need for active region disconnection in 3D kinematic dynamo simulations

2019 ◽  
Vol 627 ◽  
pp. A168 ◽  
Author(s):  
T. Whitbread ◽  
A. R. Yeates ◽  
A. Muñoz-Jaramillo
Keyword(s):  
Solar Cycle ◽  
Active Region ◽  
Convection Zone ◽  
Transport Model ◽  
Active Regions ◽  
Surface Flux ◽  
Dynamo Model ◽  
Flux Transport ◽  
Kinematic Dynamo ◽  
The Difference

In this paper we address a discrepancy between the surface flux evolution in a 3D kinematic dynamo model and a 2D surface flux transport model that has been closely calibrated to the real Sun. We demonstrate that the difference is due to the connectivity of active regions to the toroidal field at the base of the convection zone, which is not accounted for in the surface-only model. Initially, we consider the decay of a single active region, firstly in a simplified Cartesian 2D model and subsequently the full 3D model. By varying the turbulent diffusivity profile in the convection zone, we find that increasing the diffusivity – so that active regions are more rapidly disconnected from the base of the convection zone – improves the evolution of the surface field. However, if we simulate a full solar cycle, we find that the dynamo is unable to sustain itself under such an enhanced diffusivity. This suggests that in order to accurately model the solar cycle, we must find an alternative way to disconnect emerging active regions, whilst conserving magnetic flux.

scholarly journals How Good Is the Bipolar Approximation of Active Regions for Surface Flux Transport?

Solar Physics ◽  
2020 ◽  
Vol 295 (9) ◽  
Author(s):  
Anthony R. Yeates
Keyword(s):  
Dipole Moment ◽  
Active Region ◽  
Transport Model ◽  
Active Regions ◽  
Surface Flux ◽  
Flux Transport ◽  
Transport Models ◽  
Magnetic Structures ◽  
Axial Dipole ◽  
Flow Parameters

Abstract We investigate how representing active regions with bipolar magnetic regions (BMRs) affects the end-of-cycle polar field predicted by the surface flux transport model. Our study is based on a new database of BMRs derived from the SDO/HMI active region patch data between 2010 and 2020. An automated code is developed for fitting each active region patch with a BMR, matching both the magnetic flux and axial dipole moment of the region and removing repeat observations of the same region. By comparing the predicted evolution of each of the 1090 BMRs with the predicted evolution of their original active region patches, we show that the bipolar approximation leads to a 24% overestimate of the net axial dipole moment, given the same flow parameters. This is caused by neglecting the more complex multipolar and/or asymmetric magnetic structures of many of the real active regions, and may explain why previous flux transport models had to reduce BMR tilt angles to obtain realistic polar fields. Our BMR database and the Python code to extract it are freely available.

scholarly journals The balance of magnetic fluxes in active regions

1968 ◽  
Vol 35 ◽  
pp. 47-49 ◽  
Author(s):  
Jan Olof Stenflo
Keyword(s):  
Magnetic Field ◽  
Solar Cycle ◽  
Active Region ◽  
Solar Surface ◽  
Active Regions ◽  
Basic Feature ◽  
The Sun ◽  
Magnetic Disturbance ◽  
The Magnetic Field

According to modern theories of the solar cycle, active regions on the Sun are caused by a magnetic disturbance penetrating the solar surface from below. Sunspots, filaments, flares and other conspicuous events in an active region seem to be only secondary phenomena, the basic feature being the magnetic field itself.

scholarly journals Differences in the solar cycle variability of simple and complex active regions during 1996–2018

2019 ◽  
Vol 629 ◽  
pp. A45 ◽  
Author(s):  
S. Nikbakhsh ◽  
E. I. Tanskanen ◽  
M. J. Käpylä ◽  
T. Hackman
Keyword(s):  
Solar Cycle ◽  
Active Region ◽  
Time Evolution ◽  
Large Scale ◽  
Active Regions ◽  
Small Scale ◽  
Relative Role ◽  
Activity Band ◽  
Cycle 24

Aims. Our aim is to examine the solar cycle variability of magnetically simple and complex active region. Methods. We studied simple (α and β) and complex (βγ and βγδ) active regions based on the Mount Wilson magnetic classification by applying our newly developed daily approach. We analyzed the daily number of the simple active regions (SARs) and compared that to the abundance of the complex active regions (CARs) over the entire solar cycle 23 and cycle 24 until December 2018. Results. We show that CARs evolve differently over the solar cycle from SARs. The time evolution of SARs and CARs on different hemispheres also shows differences, even though on average their latitudinal distributions are shown to be similar. The time evolution of SARs closely follows that of the sunspot number, and their maximum abundance was observed to occur during the early maximum phase, while that of the CARs was seen roughly two years later. We furthermore found that the peak of CARs was reached before the latitudinal width of the activity band starts to decease. Conclusion. Our results suggest that the active region formation process is a competition between the large-scale dynamo (LSD) and the small-scale dynamo (SSD) near the surface, the former varying cyclically and the latter being independent of the solar cycle. During solar maximum, LSD is dominant, giving a preference to SARs, while during the declining phase the relative role of SSD increases. Therefore, a preference for CARs is seen due to the influence of the SSD on the emerging flux.

The Hemispheric Sign Rule of Current Helicity during the Rising Phase of Cycle 23

2000 ◽  
Vol 179 ◽  
pp. 303-306
Author(s):  
S. D. Bao ◽  
G. X. Ai ◽  
H. Q. Zhang
Keyword(s):  
Solar Cycle ◽  
Southern Hemisphere ◽  
Northern Hemisphere ◽  
Active Regions ◽  
Hemispheric Preference ◽  
Current Helicity

AbstractWe compute the signs of two different current helicity parameters (i.e., αbestandHc) for 87 active regions during the rise of cycle 23. The results indicate that 59% of the active regions in the northern hemisphere have negative αbestand 65% in the southern hemisphere have positive. This is consistent with that of the cycle 22. However, the helicity parameterHcshows a weaker opposite hemispheric preference in the new solar cycle. Possible reasons are discussed.

On-the-Fly Determination of Active Region Centers in Adaptive-Partitioning QM/MM

2020 ◽  
Author(s):  
Zenghui Yang
Keyword(s):  
Quantum Mechanics ◽  
Active Region ◽  
Molecular Mechanics ◽  
Active Regions ◽  
Available Energy ◽  
Adaptive Partitioning ◽  
Different Levels

Quantum mechanics/molecular mechanics (QM/MM) methods partition the system into active and environmental regions and treat them with different levels of theory, achieving accuracy and efficiency at the same time. Adaptive-partitioning (AP) QM/MM methods allow on-the-fly changes to the QM/MM partitioning of the system. Many of the available energy-based AP-QM/MM methods partition the system according to distances to pre-chosen centers of active regions. For such AP-QM/MM methods, I develop an adaptive-center (AC) method that allows on-the-fly determination of the centers of active regions according to general geometrical or potential-related criteria, extending the range of application of energy-based AP-QM/MM methods to systems where active regions may occur or vanish during the simulation.

scholarly journals The Evolution of the Solar Magnetic Field

2012 ◽  
Vol 10 (H16) ◽  
pp. 86-89 ◽  
Author(s):  
J. Todd Hoeksema
Keyword(s):  
Magnetic Field ◽  
Solar Cycle ◽  
Solar Magnetic Field ◽  
Coronal Holes ◽  
Active Regions ◽  
Statistical Characteristics ◽  
Field Pattern ◽  
Small Scale ◽  
Polar Caps ◽  
Magnetic Elements

AbstractThe almost stately evolution of the global heliospheric magnetic field pattern during most of the solar cycle belies the intense dynamic interplay of photospheric and coronal flux concentrations on scales both large and small. The statistical characteristics of emerging bipoles and active regions lead to development of systematic magnetic patterns. Diffusion and flows impel features to interact constructively and destructively, and on longer time scales they may help drive the creation of new flux. Peculiar properties of the components in each solar cycle determine the specific details and provide additional clues about their sources. The interactions of complex developing features with the existing global magnetic environment drive impulsive events on all scales. Predominantly new-polarity surges originating in active regions at low latitudes can reach the poles in a year or two. Coronal holes and polar caps composed of short-lived, small-scale magnetic elements can persist for months and years. Advanced models coupled with comprehensive measurements of the visible solar surface, as well as the interior, corona, and heliosphere promise to revolutionize our understanding of the hierarchy we call the solar magnetic field.

Diagnostics of Polar Field Reversal in Solar Cycle 23 Using a Flux Transport Dynamo Model

2004 ◽  
Vol 601 (2) ◽  
pp. 1136-1151 ◽  
Author(s):  
Mausumi Dikpati ◽  
Giuliana de Toma ◽  
Peter A. Gilman ◽  
Charles N. Arge ◽  
Oran R. White
Keyword(s):  
Solar Cycle ◽  
Polar Field ◽  
Dynamo Model ◽  
Flux Transport ◽  
Field Reversal ◽  
Solar Cycle 23

scholarly journals Solar Internal Rotation, the Boundary Layer Dynamo and Latitude Distribution of Activity Belts

1991 ◽  
Vol 130 ◽  
pp. 237-240
Author(s):  
G. Belvedere ◽  
M.R.E. Proctor ◽  
G. Lanzafame
Keyword(s):  
Boundary Layer ◽  
Internal Rotation ◽  
Radial Profile ◽  
Active Regions ◽  
Dynamo Model ◽  
Main Sequence Stars ◽  
Dynamo Action ◽  
Latitude Distribution ◽  
Thin Spherical Shell ◽  
And Migration

Abstract We suggest that the latitude distribution of solar activity belts and the related equatorward or poleward migration of different tracers of the solar cycle are a natural consequence of the internal radial profile of angular velocity via the working of a dynamo in the boundary layer beneath the convection zone. This has been confirmed by the results of a non-linear dynamo model in a very thin spherical shell which show that dynamo action may reasonably take place in the boundary layer and reproduce the observed surface phenomenology.Extending the argument to late main-sequence stars, it is reasonable to think that observations of the latitude distribution and migration of stellar active regions by current sophisticated techniques may make it possible to infer their internal rotation profile in a simple and direct way.

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