Limits to solar cycle predictability: Cross-equatorial flux plumes

Abstract

Context. Within the Babcock-Leighton framework for the solar dynamo, the strength of a cycle is expected to depend on the strength of the dipole moment or net hemispheric flux during the preceding minimum, which depends on how much flux was present in each hemisphere at the start of the previous cycle and how much net magnetic flux was transported across the equator during the cycle. Some of this transport is associated with the random walk of magnetic flux tubes subject to granular and supergranular buffeting, some of it is due to the advection caused by systematic cross-equatorial flows such as those associated with the inflows into active regions, and some crosses the equator during the emergence process. Aims. We aim to determine how much of the cross-equatorial transport is due to small-scale disorganized motions (treated as diffusion) compared with other processes such as emergence flux across the equator. Methods. We measure the cross-equatorial flux transport using Kitt Peak synoptic magnetograms, estimating both the total and diffusive fluxes. Results. Occasionally a large sunspot group, with a large tilt angle emerges crossing the equator, with flux from the two polarities in opposite hemispheres. The largest of these events carry a substantial amount of flux across the equator (compared to the magnetic flux near the poles). We call such events cross-equatorial flux plumes. There are very few such large events during a cycle, which introduces an uncertainty into the determination of the amount of magnetic flux transported across the equator in any particular cycle. As the amount of flux which crosses the equator determines the amount of net flux in each hemisphere, it follows that the cross-equatorial plumes introduce an uncertainty in the prediction of the net flux in each hemisphere. This leads to an uncertainty in predictions of the strength of the following cycle.

Sunspot positions, areas, and group tilt angles for 1611−1631 from observations by Christoph Scheiner

“…On some days, just a few small spots are on the other hemisphere, but on two days (one day for each group), the average polarities sit in opposite hemispheres. Near-equator groups may be interesting for the progress of the activity cycle as recently suggested by Cameron et al (2013). For the accurate period of 1618-1631, we find 18 bipolar groups having a group center latitudes of |λ| ≤ 5 • .…”

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

“…While we in our 3D dynamo model and Lemerle & Charbonneau (2017) in their coupled 2D×2D model explicitly demonstrate this, the original idea was known since the work of Charbonneau & Dikpati (2000). Recently, Cameron et al (2013) demonstrated this idea using observations, while Jiang et al (2014) for the first time quantified the effect of the tilt scatter on the polar field using a surface flux transport model. Based on this idea many authors (e.g., Choudhuri & Karak 2009;Yeates et al 2008;Olemskoy & Kitchatinov 2013) modeled irregular features of the solar cycle by including fluctuations in the BL α term of their 2D flux transport dynamo models.…”

Solar forcing for CMIP6 (v3.2)

“…Given the difficulty in predicting solar activity even one cycle ahead (Pesnell, 2012;Cameron et al, 2013), one may wonder whether it even makes sense to consider longer horizons. The solar cycle is driven by the solar dynamo, by which the dynamical interactions of flows and magnetic fields in the solar convection zone lead to periodic reversals of polarity of the solar magnetic field (Charbonneau, 2010).…”

“…Recent years have witnessed significant advances in solar dynamo modeling, and the development of several physical models . In stochastically forced kinematic dynamo models, persistence in the solar-cycle-averaged level of activity (hereafter "memory") can extend from less than one and up to three cycles, depending on details of the models and of the physical parameter regime in which they operate (e.g., St-Jean and Charbonneau, 2007;Yeates et al, 2008;Cameron et al, 2013;Muñoz-Jaramillo et al, 2013). In nonkinematic dynamo models incorporating the magnetic back reaction on large-scale inductive flows, deterministic modulation of the primary cycle amplitude can be produced, amounting to a form of memory that can extend over tens of activity cycles in a wide range of parameter regimes (e.g., Tobias, 1997;Bushby, 2006).…”