A simple stochastic model for dipole moment fluctuations in numerical dynamo simulations

Earth's axial dipole field changes in a complex fashion on many differenttime scales ranging from less than a year to tens of million years.Documenting, analysing, and replicating this intricate signalis a challenge for data acquisition, theoretical interpretation,and dynamo modelling alike. He...

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Main Authors: Domenico G. eMeduri, Johannes eWicht
Format: Article
Language:English
Published: Frontiers Media S.A. 2016-04-01
Series:Frontiers in Earth Science
Subjects:
Online Access:http://journal.frontiersin.org/Journal/10.3389/feart.2016.00038/full
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spelling doaj-f4574a661eed42d2aceb875892b163a22020-11-25T00:31:19ZengFrontiers Media S.A.Frontiers in Earth Science2296-64632016-04-01410.3389/feart.2016.00038182840A simple stochastic model for dipole moment fluctuations in numerical dynamo simulationsDomenico G. eMeduri0Johannes eWicht1Max Planck Institute for Solar System ResearchMax Planck Institute for Solar System ResearchEarth's axial dipole field changes in a complex fashion on many differenttime scales ranging from less than a year to tens of million years.Documenting, analysing, and replicating this intricate signalis a challenge for data acquisition, theoretical interpretation,and dynamo modelling alike. Here we explore whether axial dipole variationscan be described by the superposition of a slow deterministic driftand fast stochastic fluctuations, i.e. by a Langevin-type system.The drift term describes the time averaged behaviour of the axial dipole variations,whereas the stochastic part mimics complex flow interactions over convective time scales.The statistical behaviour of the system is described by a Fokker-Planck equation whichallows useful predictions, including the average rates of dipole reversals and excursions.We analyse several numerical dynamo simulations, most of which havebeen integrated particularly long in time, and also the palaeomagneticmodel PADM2M which covers the past 2 Myr.The results show that the Langevin description provides a viable statistical modelof the axial dipole variations on time scales longer than about 1 kyr.For example, the axial dipole probability distribution and the average reversalrate are successfully predicted.The exception is PADM2M where the stochastic model reversal rate seems too low.The dependence of the drift on the axial dipolemoment reveals the nonlinear interactions that establish thedynamo balance. A separate analysis of inductive and diffusive magnetic effectsin three dynamo simulations suggests that the classical quadraticquenching of induction predicted by mean-field theory seems at work.http://journal.frontiersin.org/Journal/10.3389/feart.2016.00038/fullnumerical simulationstatistical analysisStochastic Modelgeomagnetic fieldGeodynamoField reversals
collection DOAJ
language English
format Article
sources DOAJ
author Domenico G. eMeduri
Johannes eWicht
spellingShingle Domenico G. eMeduri
Johannes eWicht
A simple stochastic model for dipole moment fluctuations in numerical dynamo simulations
Frontiers in Earth Science
numerical simulation
statistical analysis
Stochastic Model
geomagnetic field
Geodynamo
Field reversals
author_facet Domenico G. eMeduri
Johannes eWicht
author_sort Domenico G. eMeduri
title A simple stochastic model for dipole moment fluctuations in numerical dynamo simulations
title_short A simple stochastic model for dipole moment fluctuations in numerical dynamo simulations
title_full A simple stochastic model for dipole moment fluctuations in numerical dynamo simulations
title_fullStr A simple stochastic model for dipole moment fluctuations in numerical dynamo simulations
title_full_unstemmed A simple stochastic model for dipole moment fluctuations in numerical dynamo simulations
title_sort simple stochastic model for dipole moment fluctuations in numerical dynamo simulations
publisher Frontiers Media S.A.
series Frontiers in Earth Science
issn 2296-6463
publishDate 2016-04-01
description Earth's axial dipole field changes in a complex fashion on many differenttime scales ranging from less than a year to tens of million years.Documenting, analysing, and replicating this intricate signalis a challenge for data acquisition, theoretical interpretation,and dynamo modelling alike. Here we explore whether axial dipole variationscan be described by the superposition of a slow deterministic driftand fast stochastic fluctuations, i.e. by a Langevin-type system.The drift term describes the time averaged behaviour of the axial dipole variations,whereas the stochastic part mimics complex flow interactions over convective time scales.The statistical behaviour of the system is described by a Fokker-Planck equation whichallows useful predictions, including the average rates of dipole reversals and excursions.We analyse several numerical dynamo simulations, most of which havebeen integrated particularly long in time, and also the palaeomagneticmodel PADM2M which covers the past 2 Myr.The results show that the Langevin description provides a viable statistical modelof the axial dipole variations on time scales longer than about 1 kyr.For example, the axial dipole probability distribution and the average reversalrate are successfully predicted.The exception is PADM2M where the stochastic model reversal rate seems too low.The dependence of the drift on the axial dipolemoment reveals the nonlinear interactions that establish thedynamo balance. A separate analysis of inductive and diffusive magnetic effectsin three dynamo simulations suggests that the classical quadraticquenching of induction predicted by mean-field theory seems at work.
topic numerical simulation
statistical analysis
Stochastic Model
geomagnetic field
Geodynamo
Field reversals
url http://journal.frontiersin.org/Journal/10.3389/feart.2016.00038/full
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