Polar Network Index as a Magnetic Proxy for the Solar Cycle Studies

Priyal, Muthu; Banerjee, D.; Karak, Bidya Binay; Muñoz-Jaramillo, Andrés; Ravindra, B.; Choudhuri, Arnab Rai; Singh, Jagdev

doi:10.1088/2041-8205/793/1/l4

Cited by 54 publications

(35 citation statements)

References 24 publications

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“…However, they largely average out over many BMRs; otherwise, we would not get a strong correlation between the polar flux (n) and the BMR flux (n+1) as listed in Table 2. This is in agreement with the correlation obtained from the observed polar field data ) and from different proxies of the polar field (Muñoz-Jaramillo et al 2013;Priyal et al 2014). In fact, this correlation is a popular basis for the solar cycle prediction (Schatten et al 1978).…”

Section: Steady Dynamo Solutionsupporting

confidence: 90%

“…These tilted BMRs, when they decay and disperse on the solar surface, produce a large-scale poloidal field, as proposed by Babcock (1961) and Leighton (1964). Recent high-quality BMR (area, tilt, separation, etc) and polar field data (measured both directly via polarization and indirectly through different proxies, including polar faculae and active networks), suggest that this process is sufficient to maintain the observed polar flux in the Sun (Dasi-Espuig et al 2010;Kitchatinov & Olemskoy 2011;Muñoz-Jaramillo et al 2013;Priyal et al 2014). …”

Section: Introductionmentioning

confidence: 74%

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Solar Cycle Variability Induced by Tilt Angle Scatter in a Babcock–Leighton Solar Dynamo Model

Karak

Miesch

2017

ApJ

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We present results from a three-dimensional Babcock-Leighton dynamo model that is sustained by the explicit emergence and dispersal of bipolar magnetic regions (BMRs). On average, each BMR has a systematic tilt given by Joy's law. Randomness and nonlinearity in the BMR emergence of our model produce variable magnetic cycles. However, when we allow for a random scatter in the tilt angle to mimic the observed departures from Joy's law, we find more variability in the magnetic cycles. We find that the observed standard deviation in Joy's law of σ δ = 15• produces a variability comparable to observed solar cycle variability of ∼ 32%, as quantified by the sunspot number maxima between 1755-2008. We also find that tilt angle scatter can promote grand minima and grand maxima. The time spent in grand minima for σ δ = 15• is somewhat less than that inferred for the Sun from cosmogenic isotopes (about 9% compared to 17%). However, when we double the tilt scatter to σ δ = 30• , the simulation statistics are comparable to the Sun (∼18% of the time in grand minima and ∼ 10% in grand maxima). Though the Babcock-Leighton mechanism is the only source of poloidal field, we find that our simulations always maintain magnetic cycles even at large fluctuations in the tilt angle. We also demonstrate that tilt quenching is a viable and efficient mechanism for dynamo saturation; a suppression of the tilt by only 1-2• is sufficient to limit the dynamo growth. Thus, any potential observational signatures of tilt quenching in the Sun may be subtle.

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Section: Steady Dynamo Solutionsupporting

confidence: 90%

Section: Introductionmentioning

confidence: 74%

Solar Cycle Variability Induced by Tilt Angle Scatter in a Babcock–Leighton Solar Dynamo Model

Karak

Miesch

2017

ApJ

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“…Observatories at Mount Wilson and Kodaikanal provide the tilt angle information of sunspot groups in the intervals 1917-1985 and 1906-1987, respectively. Direct observational data for the Sun's polar magnetic field are available only from mid-1970s (mainly from Wilcox Solar Observatory), with polar faculae and network index providing indirect determinations back to 1905 (Muñoz Jaramillo et al 2012;Priyal et al 2014, and references therein). and adopted an idealized method of assimilating the observed sunspot records (RGO/SOON data) into the poloidal flux of a FTD model.…”

Section: Data Assimilation To Flux Transport Dynamosmentioning

confidence: 99%

Flux Transport Dynamos: From Kinematics to Dynamics

et al. 2014

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Over the past several decades, Flux-Transport Dynamo (FTD) models have emerged as a popular paradigm for explaining the cyclic nature of solar magnetic activity. Their defining characteristic is the key role played by the mean meridional circulation in transporting magnetic flux and thereby regulating the cycle period. Most FTD models also incorporate the so-called Babcock-Leighton (BL) mechanism in which the mean poloidal field is produced by the emergence and subsequent dispersal of bipolar active regions. This feature is well grounded in solar observations and provides a means for assimilating observed surface flows and fields into the models in order to forecast future solar activity, to identify model biases, and to clarify the underlying physical processes. Furthermore, interpreting historical sunspot records within the context of FTD models can potentially provide insight into why cycle features such as amplitude and duration vary and what causes extreme events such as Grand Minima. Though they are generally robust in a modeling sense and make good contact with observed cycle features, FTD models rely on input physics that B.B. Karak et al. is only partially constrained by observation and that neglects the subtleties of convective transport, convective field generation, and nonlinear feedbacks. Here we review the formulation and application of FTD models and assess our current understanding of the input physics based largely on complementary 3D MHD simulations of solar convection, dynamo action, and flux emergence.

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“…Based on the available data of the observed polar field, DR and other surface features, it is expected that the solar dynamo is primarily of αΩ type (Cameron & Schüssler 2015). In recent years, it has been realized that it is the Babcock-Leighton process which acts like an α effect to generate the poloidal field through the decay and dispersal of tilted bipolar magnetic regions (BMRs) (Dasi-Espuig et al 2010;Kitchatinov & Olemskoy 2011a;Muñoz-Jaramillo et al 2013;Priyal et al 2014). Although in the Sun, DR is the dominating source of the toroidal field, a weak toroidal field might be generated through the α effect.…”

Section: Introductionmentioning

confidence: 99%

Stellar dynamos with solar and antisolar differential rotations: Implications to magnetic cycles of slowly rotating stars

Karak

Tomar

Vashishth

2019

Monthly Notices of the Royal Astronomical Society

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Simulations of magnetohydrodynamics convection in slowly rotating stars predict antisolar differential rotation (DR) in which the equator rotates slower than poles. This anti-solar DR in the usual αΩ dynamo model does not produce polarity reversal. Thus, the features of large-scale magnetic fields in slowly rotating stars are expected to be different than stars having solar-like DR. In this study, we perform mean-field kinematic dynamo modelling of different stars at different rotation periods. We consider anti-solar DR for the stars having rotation period larger than 30 days and solar-like DR otherwise. We show that with particular α profiles, the dynamo model produces magnetic cycles with polarity reversals even with the anti-solar DR provided, the DR is quenched when the toroidal field grows considerably high and there is a sufficiently strong α for the generation of toroidal field. Due to the anti-solar DR, the model produces an abrupt increase of magnetic field exactly when the DR profile is changed from solar-like to anti-solar. This enhancement of magnetic field is in good agreement with the stellar observational data as well as some global convection simulations. In the solar-like DR branch, with the decreasing rotation period, we find the magnetic field strength increases while the cycle period shortens. Both of these trends are in general agreement with observations. Our study provides additional support for the possible existence of anti-solar DR in slowly rotating stars and the presence of unusually enhanced magnetic fields and possibly cycles which are prone to production of superflare.

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Polar Network Index as a Magnetic Proxy for the Solar Cycle Studies

Cited by 54 publications

References 24 publications

Solar Cycle Variability Induced by Tilt Angle Scatter in a Babcock–Leighton Solar Dynamo Model

Solar Cycle Variability Induced by Tilt Angle Scatter in a Babcock–Leighton Solar Dynamo Model

Flux Transport Dynamos: From Kinematics to Dynamics

Stellar dynamos with solar and antisolar differential rotations: Implications to magnetic cycles of slowly rotating stars

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