4.2 <img width="12" alt="a" height="10" class="10-120x-x-b" src="cmmib10-c-b.gif"><img src="cmbx12-a.gif" alt="_O_" class="12x-x-a" width="13" height="13"> mean-field models

4.2 $a_O_$ mean-field models

4.2.1 Calculating the $a$ -effect and turbulent diffusivity

Mean-field electrodynamics is a subject well worth its own full-length review, so the foregoing discussion will be limited to the bare essentials. Detailed discussion of the topic can be found in Krause and Rädler (1980 ); Moffatt (1978 ), and in the recent review article by Hoyng (2003 ).

The task at hand is to calculate the components of the $a$ and $b$ tensor in terms of the statistical properties of the underlying turbulence. A particularly simple case is that of homogeneous, weakly isotropic turbulence, which reduces the $a$ and $b$ tensor to simple scalars, so that the mean electromotive force becomes

$E = a - jT \~/ × . (20)$

This is the form commonly used in solar dynamo modelling, even though turbulence in the solar interior is most likely inhomogeneous and anisotropic. Moreover, hiding in the above expressions is the assumption that the small-scale magnetic Reynolds number $vl/j$ is much smaller than unity, where $3 -1 v ~ 10 cm s$ and $9 l ~ 10 cm$ are characteristic velocities and length scales for the dominant turbulent eddies, as estimated, e.g., from mixing length theory. With $4 2 -1 j ~ 10 cm s$ , one finds $vl/j ~ 108$ , so that on that basis alone Equation (20

) should be dubious already. In the kinematic regime, $a$ and $b$ are independent of the magnetic field fluctuations, and end up simply proportional to the averaged kinetic helicity and square fluctuation amplitude:

$tc ' ' a ~ - 3-, (21) tc jT ~ --<u'.u'> , (22) 3$

where $tc$ is the correlation time of the turbulent motions. Order-of-magnitude estimates of the scalar coefficients yield $a ~ _O_l$ and $jT ~ vl$ , where $_O_$ is the solar angular velocity. At the base of the solar convection zone, one then finds $a ~ 103 cm s- 1$ and $jT ~ 1012 cm2 s- 1$ , these being understood as very rough estimates. Because the kinetic helicity may well change sign along the longitudinal (averaging) direction, thus leading to cancellation, the resulting value of $a$ may be much smaller than its r.m.s. deviation about the longitudinal mean. In contrast the quantity being averaged on the right hand side of Equation (22

) is positive definite, so one would expect a more “stable” mean value (see Hoyng, 1993

; Ossendrijver et al., 2001

, for further discussion). At any rate, difficulties in computing $a$ and $jT$ from first principle (whether as scalars or tensors) have led to these quantities often being treated as adjustable parameters of mean-field dynamo models, to be adjusted (within reasonable bounds) to yield the best possible fit to observed solar cycle characteristics, most importantly the cycle period. One finds in the literature numerical values in the approximate ranges $10- 103 cm s-1$ for $a$ and $1010 -1013 cm2 s- 1$ for $jT$ .

The cyclonic character of the $a$ -effect also indicates that it is equatorially antisymmetric and positive in the Northern solar hemisphere, except perhaps at the base of the convective envelope, where the rapid variation of the turbulent velocity with depth can lead to sign change. These expectations have been confirmed in a general sense by theory and numerical simulations (see, e.g., Rüdiger and Kitchatinov, 1993 ; Brandenburg et al., 1990 ; Ossendrijver et al., 2001 ).

Leaving the kinematic regime, it is expected that both $a$ and $b$ should depend on the strength of the magnetic field, since magnetic tension will resist deformation by the small-scale turbulent fluid motions. The groundbreaking numerical MHD simulations of Pouquet et al. (1976 ) suggested that Equation (21 ) should be replaced by something like

$a ~ - tc[<u'. \~/ × u'>- <a'.\ ~/ × a'>], (23) 3$

where $a'= b'/ V~ 4pr-$ is the Alfvén speed based on the small-scale magnetic component (see also Durney et al., 1993

; Blackman and Brandenburg, 2002

). This is rarely used in solar cycle modelling, since the whole point of the mean-field approach is to avoid dealing explicitly with the small-scale, fluctuating components. On the other hand, something is bound to happen when the growing dynamo-generated mean magnetic field reaches a magnitude such that its energy per unit volume is comparable to the kinetic energy of the underlying turbulent fluid motions. Denoting this equipartition field strength by $Beq$ , one often introduces an ad hoc nonlinear dependency of $a$ (and sometimes $jT$ as well) directly on the mean-field $$ by writing:

This expression “does the right thing”, in that $a --> 0$ as $$ starts to exceed $Beq$ . It remains an extreme oversimplification of the complex interaction between flow and field that characterizes MHD turbulence, but its wide usage in solar dynamo modeling makes it a nonlinearity of choice for the illustrative purpose of this section.

4.2.2 The $a_O_$ dynamo equations

Adding this contribution to the MHD induction equation leads to the following form for the axisymmetric mean-field dynamo equations:

$( ) @<A-> = (j + jT) \ ~/ 2 - -1- <A >- up-. \~/ (p <A >) + a , (25) @t ----------- ---p2------ p - - turbulent diffusion MFE source ( ) ( ) @<B-> = (j + jT) \ ~/ 2 - -1- +1-@p--<B->@(j-+-jT)- pup . \~/ <B->- - \~/ .up @t ----------- ---p2------ p----@r-- ---@r--- p turbulent diffusion turbulent diamagnetic transport + p(\ ~/ -×-(<A >^ef))-. \~/ _O_ + \~/ -×-[a\ ~/ -× (<A->^ef)], (26) shearing MFE source$

where, in general, $jT » j$ . There are source terms on both right hand sides, so that dynamo action is now possible in principle. The relative importance of the $a$ -effect and shearing terms in Equation (26

) is measured by the ratio of the two dimensionless dynamo numbers

where, in the spirit of dimensional analysis, $a0$ , $j0$ , and $(D_O_)0$ are “typical” values for the $a$ -effect, turbulent diffusivity, and angular velocity contrast. These quantities arise naturally in the non-dimensional formulation of the mean-field dynamo equations, when time is expressed in units of the magnetic diffusion time $t$ based on the envelope (turbulent) diffusivity:

In the solar case, it is usually estimated that $Ca « C_O_$ , so that the $a$ -term is neglected in Equation (26

); this results in the class of dynamo models known as $a_O_$ dynamo, which will be the only ones discussed here⁵ .

4.2.3 Eigenvalue problems and initial value problems

With the large-scale flows, turbulent diffusivity and $a$ -effect considered given, Equations (25 , 26 ) become truly linear in $A$ and $B$ . It becomes possible to seek eigensolutions in the form

Substitution of these expressions into Equations (25

, 26

) yields an eigenvalue problem for $s$ and associated eigenfunction ${a,b}$ . The real part $s =_ Re s$ is then a growth rate, and the imaginary part $w =_ Im s$ an oscillation frequency. One typically finds that $s < 0$ until the product $Ca × C_O_$ exceeds a certain critical value $Dcrit$ beyond which $s > 0$ , corresponding to a growing solutions. Such solutions are said to be supercritical, while the solution with $s = 0$ is critical.

Clearly exponential growth of the dynamo-generated magnetic field must cease at some point, once the field starts to backreact on the flow through the Lorentz force. This is the general idea embodied in $a$ -quenching. If $a$ -quenching - or some other nonlinearity - is included, then the dynamo equations are usually solved as an initial-value problem, with some arbitrary low-amplitude seed field used as initial condition. Equations (25 , 26 ) are then integrated forward in time using some appropriate time-stepping scheme. A useful quantity to monitor in order to ascertain saturation is the magnetic energy within the computational domain:

4.2.4 Dynamo waves

One of the most remarkable property of the (linear) $a_O_$ dynamo equations is that they support travelling wave solutions. This was first demonstrated in Cartesian geometry by Parker (1955 ), who proposed that a latitudinally-travelling “dynamo wave” was at the origin of the observed equatorward drift of sunspot emergences in the course of the cycle. This finding was subsequently shown to hold in spherical geometry, as well as for non-linear models (Yoshimura, 1975 ; Stix, 1976 ). Dynamo waves⁶ travel in a direction $s$ given by

$s = a \~/ _O_ × ^ef, (31)$

a result now known as the “Parker-Yoshimura sign rule”. Recalling the rather complex form of the helioseismically inferred solar internal differential rotation (cf. Figure 5

), even an $a$ -effect of uniform sign in each hemisphere can produce complex migratory patterns, as will be apparent in the illustrative $a_O_$ dynamo solutions to be discussed shortly. Note already at this juncture that if the seat of the dynamo is to be identified with the low-latitude portion of the tachocline, and if the latter is thin enough for the (positive) radial shear therein to dominate over the latitudinal shear, then equatorward migration of dynamo waves will require a negative $a$ -effect in the low latitudes of the Northern solar hemisphere.

4.2.5 Representative results

We first consider $a_O_$ models without meridional circulation ( $up = 0$ in Equations (25 , 26 )), with the $a$ -term omitted in Equation (26 ), and using the diffusivity profile and angular velocity profile of Figure 5 . We will investigate the behavior of $a_O_$ models with the $a$ -effect operating throughout the bulk of the convective envelope (red line in Figure 6 ), as well as with an $a$ -effect concentrated just above the core-envelope interface (green line in Figure 6 ). We also consider two latitudinal dependencies, namely $a oc cosh$ , which is the “minimal” possible latitudinal dependency compatible with the required equatorial antisymmetry of the Coriolis force, and an $a$ -effect concentrated towards the equator⁷ via an assumed latitudinal dependency $a oc sin2 hcos h$ .

Figure 6:

Radial variations of the $a$ -effect for the two classes of mean-field models considered in Section 4.2.5. The magnetic diffusivity profile is again indicated by a dash-dotted line, and the core-envelope interface by a dotted line.

Figure 7

shows a selection of such dynamo solutions, in the form of time-latitude diagrams of the toroidal field extracted at the core-envelope interface, here $rc/Ro . = 0.7$ . If sunspot-producing toroidal flux ropes form in regions of peak toroidal field strength, and if those ropes rise radially to the surface, then such diagrams are directly comparable to the sunspot butterfly diagram of Figure 3

. All models have $C_O_ = 25000$ , $|Ca |= 10$ , $jT/jc = 10$ , and $jT = 5 × 1011 cm2 s-1$ , which leads to $t -~ 300 yr$ . To facilitate comparison between solutions, here antisymmetric parity was imposed via the boundary condition at the equator.

Figure 7:

Northern hemisphere time-latitude (“butterfly”) diagrams for a selection of $a_O_$ dynamo solutions, constructed at the depth $rc/Ro . = 0.7$ corresponding to the core-envelope interface. Isocontours of toroidal field are normalized to their peak amplitudes, and plotted for increments $DB/ max(B) = 0.2$ , with yellow-to-red (green-to-blue) contours corresponding to $B > 0$ ( $< 0$ ). All but the first solution have the $a$ -effect concentrated at the base of the envelope, with a latitude dependence as given above each panel. Other model ingredients as in Figure 5

. Note the co-existence of two distinct, cycles in the solution shown in Panel B. Four corresponding animations are available in Resource 1.

Models using the radially broad, full convection zone $a$ -effect (Panel A of Figure 7

) feed mostly on the latitudinal shear in the envelope, so that the dynamo mode propagates radially upward in the envelope, with some latitudinal propagation in the tachocline only at the onset of the cycle (see animation). Models with positive $Ca$ nonetheless yield oscillatory solutions, but those with $Ca < 0$ produce steady modes over a wide range of parameter values. Models using an $a$ -effect concentrated at the base of the envelope (Panels B through D), on the other hand, are powered by the radial shear therein, and show the expected tilt in the butterfly diagrams, as expected from the Parker-Yoshimura sign rule (cf. Section 4.2.4). Note that even for an equatorially-concentrated $a$ -effect (Panels B and D), a strong polar branch is nonetheless apparent in the butterfly diagrams, a direct consequence of the stronger radial shear present at high latitudes in the tachocline (see also corresponding animations).

It is noteworthy that co-existing dynamo branches, as in Panel B of Figure 7 , can have distinct dynamo periods, which in nonlinearly saturated solutions leads to long-term amplitude modulation. This is typically not expected in dynamo models where the only nonlinearity present is a simple algebraic quenching formula such as Equation (24 ). A portion of the magnetic energy time-series for that solution is shown in Panel A of Figure 8 to illustrate the effect. Note that this does not occur for the $Ca < 0$ solution (Panel B of Figure 8 ), where both branches propagate away from each other, but share a common latitude of origin and so are phased-locked at the onset (cf. Panel D of Figure 7 ).

Figure 8:

Time series of magnetic energy in four mean-field $a_O_$ dynamo solutions. Panels A and B show the time series associated with the solutions shown in Panels B and D of Figure 7

(base CZ, $2 a ~ sin h cosh$ , $Ca = ± 10$ ). Note the initial phase of exponential growth of the magnetic field, followed by a saturation phase characterized here by an (atypical) periodic modulation in the case of the solution in Panel A. Panels C and D show time series for two interface dynamo solutions (see Section 4.3 and Figure 10

) for two diffusivity ratios. The energy scale is expressed in arbitrary units, but is consistent across all four panels.

A common property of all oscillatory $a_O_$ solutions discussed so far is that their period, for given values of the dynamo numbers $Ca$ , $C_O_$ , is inversely proportional to the numerical value adopted for the (turbulent) magnetic diffusivity $jT$ . The ratio of poloidal-to-toroidal field strength, in turn, is found to scale as some power (usually close to $1/2$ ) of the ratio $Ca/C_O_$ , at a fixed value of the product $Ca × C_O_$ .

Vector magnetograms of sunspots active regions make it possible to estimate the current helicity $j .B$ which is closely related to the usual magnetic helicity $A .B$ , and the amount of twist in the sunspot-forming toroidal flux ropes (see, e.g., Hagyard and Pevtsov, 1999 , and references therein). Upon assuming that this current helicity reflects that of the diffuse, dynamo-generated magnetic field from which the flux ropes formed, one obtains another useful constraint on dynamo models. In the context of classical $a_O_$ mean-field models, predominantly negative current helicity in the N-hemisphere, in agreement with observations, is usually obtained for models with negative $a$ -effect relying primarily on positive radial shear at the equator (see Gilman and Charbonneau, 1999 , and discussion therein).

The models discussed above are based on rather minimalistics and partly ad hoc assumptions on the form of the $a$ -effect. More elaborate models have been proposed, relying on calculations of the full $a$ -tensor based on some underlying turbulence models. While this approach usually displaces the ad hoc assumptions away from the $a$ -effect and into the turbulence model, it has the definite advantage of offering an internally consistent approach to the calculation of turbulent diffusivities and large-scale flows. Rüdiger and Brandenburg (1995 ) remain a good example of the current state-of-the-art in this area; see also Rüdiger and Arlt (2003 ), and references therein.

4.2.6 Critical assessment

From a practical point of view, the outstanding success of the mean-field $a_O_$ model remains its robust explanation of the observed equatorward drift of toroidal field-tracing sunspots in the course of the cycle in terms of a dynamo-wave. On the theoretical front, the model is also buttressed by mean-field electrodynamics which, in principle, offers a physically sound theory from which to compute the (critical) $a$ -effect and magnetic diffusivity. The models’ primary uncertainties turn out to lie at that level, in that the application of the theory to the Sun in a tractable manner requires additional assumptions that are most certainly not met under solar interior conditions. Those uncertainties are exponentiated when taking the theory into the nonlinear regime, to calculate the dependence of the $a$ -effect and diffusivity on the magnetic field strength. This latter problem remains very much open at this writing.

4.2 mean-field models

4.2.1 Calculating the -effect and turbulent diffusivity

4.2.2 The dynamo equations