Exploring the reliability of polar field rise rate as a precursor for an early prediction of solar cycle

Abstract

The prediction of the strength of an upcoming solar cycle has been a long-standing challenge in the field of solar physics. The inherent stochastic nature of the underlying solar dynamo makes the strength of the solar cycle vary in a wide range. Till now, the polar precursor methods and the dynamo simulations, that uses the strength of the polar field at the cycle minimum to predict the strength of the following cycle has gained reasonable consensus by providing convergence in the predictions for solar cycles 24 and 25. Recently, it has been shown that just by using the observed correlation of the polar field rise rate with the peak of the polar field at the cycle minimum and the amplitude of the following cycle, a reliable prediction can be made much earlier than the cycle minimum. In this work, we perform surface flux transport (SFT) simulations to explore the robustness of this correlation against the stochastic fluctuations of BMR tilt properties including anti-Joy and anti-Hale type anomalous BMRs, and against the variation of meridional flow speed. We find that the observed correlation is a robust feature of the solar cycles and thus it can be utilized for a reliable prediction of solar cycle much earlier than the cycle minimum—the usual landmark of the solar cycle prediction.

An Improved Prediction of Solar Cycles 25 and 26 Using the Informer Model: Gnevyshev Peaks and North–South Asymmetry

“…The article points out that the most effective prediction methods support the Babcock-Leighton solar dynamo mechanism, viewing it as the main driving force behind the variations in the solar cycle, and strengthening the flux transport paradigm, considering it a useful tool for modeling solar-stellar magnetism. Biswas et al (2023a) studied the correlation between the rise rate of the polar magnetic field and the amplitude of the following cycle, using surface flux transport (SFT) simulations to explore the robustness of this correlation against stochastic fluctuations in the tilt properties of the bipolar magnetic region (BMR), including anti-Joy and anti-Hale anomalous BMR, and changes in meridional flow speed. This robust correlation allows for reliable prediction of solar cycles.…”

“…The methods for predicting a solar cycle can be categorized into three types (Petrovay 2010(Petrovay , 2020. The first type is the precursor methods, which rely on measurements of solar activity indicators or magnetic fields at a specific period to predict the maximum amplitude of the next solar cycle (McIntosh et al 2020;Miao et al 2020;Kumar et al 2021;Biswas et al 2023a;Asensio Ramos et al 2023). Common precursors include the polar magnetic field, the geomagnetic indices, and the interplanetary precursors (Ermolli et al 2014;Asikainen & Mantere 2023).…”

Toroidal Flux Loss due to Flux Emergence Explains why Solar Cycles Rise Differently but Decay in a Similar Way

“…Where, s = r sin θ , A is the magnetic potential of the poloidal magnetic field, B is the toroidal magnetic field. A detailed discussion about the model parameters for this particular work can be found in Biswas et al (2022).…”