Geodynamo Simulations—How Realistic Are They?

Glatzmaier, Gary A.

doi:10.1146/annurev.earth.30.091201.140817

Cited by 134 publications

(109 citation statements)

References 61 publications

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“…However, Ekman number and magnetic Prandtl number of a numerical model already fix the ratio between the rotation period and t λ to E/Pm = λ/ L 2 which is typically many orders of magnitude too large. The described field strength scaling therefore amounts to an extrapolation of E/Pm, sometimes called the magnetic Ekman number E λ , to the much smaller planetary values (Glatzmaier 2002). Realistic flow amplitudes are assumed for realistic magnetic Reynolds numbers when t λ serves to rescale time.…”

Section: Boundary Conditions and Driving Modesmentioning

confidence: 99%

“…Several publications provide extensive overviews of the different aspects in numerical dynamo simulations (Braginsky and Roberts 1995;Jones 2000Jones , 2007Glatzmaier 2002) and discuss their success in modeling the geomagnetic field (Kono and Roberts 2002;Christensen and Wicht 2007). Here, we concentrate on more recent developments that mainly concern the geodynamo.…”

Section: Introductionmentioning

confidence: 99%

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Theory and Modeling of Planetary Dynamos

Wicht

Tilgner

2010

Space Sci Rev

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Numerical dynamo models are increasingly successful in modeling many features of the geomagnetic field. Moreover, they have proven to be a useful tool for understanding how the observations connect to the dynamo mechanism. More recently, dynamo simulations have also ventured to explain the surprising diversity of planetary fields found in our solar system. Here, we describe the underlying model equations, concentrating on the Boussinesq approximations, briefly discuss the numerical methods, and give an overview of existing model variations. We explain how the solutions depend on the model parameters and introduce the primary dynamo regimes. Of particular interest is the dependence on the Ekman number which is many orders of magnitude too large in the models for numerical reasons. We show that a minor change in the solution seems to happen at E = 3×10 −6 whose significance, however, needs to be explored in the future. We also review three topics that have been a focus of recent research: field reversal mechanisms, torsional oscillations, and the influence of Earth's thermal mantle structure on the dynamo. Finally we discuss the possibility of tidally or precession driven planetary dynamos.

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Section: Boundary Conditions and Driving Modesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Theory and Modeling of Planetary Dynamos

Wicht

Tilgner

2010

Space Sci Rev

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“…It is certainly true that impressive numerical results, including the occurrence of polarity reversals, have been achieved by a number of fully coupled threedimensional ͑3D͒ geodynamo models during the past decade. 24 However, most of these models are still working in parameter regions far away from those of the Earth and/or with rather oversimplified models of turbulence, such as artificial hyperviscosities. Only recently has more effort been spent on applying up-to-date methods of subgrid scale modeling to the geodynamo, including large-eddy-simulation ͑LES͒ models 25,26 and RANS models.…”

Section: Introductionmentioning

confidence: 99%

Coupled fluid-flow and magnetic-field simulation of the Riga dynamo experiment

et al. 2006

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Magnetic fields of planets, stars, and galaxies result from self-excitation in moving electroconducting fluids, also known as the dynamo effect. This phenomenon was recently experimentally confirmed in the Riga dynamo experiment ͓A. Gailitis et al., Phys. Rev. Lett. 84, 4365 ͑2000͒; A. Gailitis et al., Physics of Plasmas 11, 2838 ͑2004͔͒, consisting of a helical motion of sodium in a long pipe followed by a straight backflow in a surrounding annular passage, which provided adequate conditions for magnetic-field self-excitation. In this paper, a first attempt to simulate computationally the Riga experiment is reported. The velocity and turbulence fields are modeled by a finite-volume Navier-Stokes solver using a Reynolds-averaged-Navier-Stokes turbulence model. The magnetic field is computed by an Adams-Bashforth finite-difference solver. The coupling of the two computational codes, although performed sequentially, provides an improved understanding of the interaction between the fluid velocity and magnetic fields in the saturation regime of the Riga dynamo experiment under realistic working conditions.

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“…One approach is the "kitchen sink" approach, that is, try to perform quasi-realistic numerical experiments to match observational features with as realistic of conditions as possible given numerical limitations (e.g. Glatzmaier 2002). A second approach is to carry out semi-empirical model calculations based on linear theories but with dynamo transport coefficients empirically tuned to match general observational features and cycle periods (e,g, Dikpati & Gilman 2009; Charbonneau 2013), and without going after the physics of nonlinear quenching.…”

Section: Types Of Dynamos and Approaches To Study Themmentioning

confidence: 99%

Magnetic Helicity and Large Scale Magnetic Fields: A Primer

Blackman¹

2016

Space Sciences Series of ISSI

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Magnetic fields of laboratory, planetary, stellar, and galactic plasmas commonly exhibit significant order on large temporal or spatial scales compared to the otherwise random motions within the hosting system. Such ordered fields can be measured in the case of planets, stars, and galaxies, or inferred indirectly by the action of their dynamical influence, such as jets. Whether large scale fields are amplified in situ or a remnant from previous stages of an object's history is often debated for objects without a definitive magnetic activity cycle. Magnetic helicity, a measure of twist and linkage of magnetic field lines, is a unifying tool for understanding large scale field evolution for both mechanisms of origin. Its importance stems from its two basic properties: (1) magnetic helicity is typically better conserved than magnetic energy; and (2) the magnetic energy associated with a fixed amount of magnetic helicity is minimized when the system relaxes this helical structure to the largest scale available. Here I discuss how magnetic helicity has come to help us understand the saturation of and sustenance of large scale dynamos, the need for either local or global helicity fluxes to avoid dynamo quenching, and the associated observational consequences. I also discuss how magnetic helicity acts as a hindrance to turbulent diffusion of large scale fields, and thus a helper for fossil remnant large scale field origin models in some contexts. I briefly discuss the connection between large scale fields and accretion disk theory as well. The goal here is to provide a conceptual primer to help the reader efficiently penetrate the literature.

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Geodynamo Simulations—How Realistic Are They?

Cited by 134 publications

References 61 publications

Theory and Modeling of Planetary Dynamos

Theory and Modeling of Planetary Dynamos

Coupled fluid-flow and magnetic-field simulation of the Riga dynamo experiment

Magnetic Helicity and Large Scale Magnetic Fields: A Primer

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