A secular variation candidate model for IGRF-13 based on Swarm data and ensemble inverse geodynamo modelling
Abstract This paper describes the design of a candidate secular variation model for the 13th generation of the International Geomagnetic Reference Field. This candidate is based upon the integration of an ensemble of 100 numerical models of the geodynamo between epochs 2019.0 and 2025.0. The only di...
Main Authors: | , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
SpringerOpen
2021-02-01
|
Series: | Earth, Planets and Space |
Subjects: | |
Online Access: | https://doi.org/10.1186/s40623-020-01309-9 |
id |
doaj-92f75111f09640ccb43c93a79bb9eddd |
---|---|
record_format |
Article |
spelling |
doaj-92f75111f09640ccb43c93a79bb9eddd2021-02-14T12:47:18ZengSpringerOpenEarth, Planets and Space1880-59812021-02-0173111610.1186/s40623-020-01309-9A secular variation candidate model for IGRF-13 based on Swarm data and ensemble inverse geodynamo modellingAlexandre Fournier0Julien Aubert1Vincent Lesur2Guillaume Ropp3Université de Paris, Institut de Physique du Globe de Paris, CNRSUniversité de Paris, Institut de Physique du Globe de Paris, CNRSUniversité de Paris, Institut de Physique du Globe de Paris, CNRSUniversité de Paris, Institut de Physique du Globe de Paris, CNRSAbstract This paper describes the design of a candidate secular variation model for the 13th generation of the International Geomagnetic Reference Field. This candidate is based upon the integration of an ensemble of 100 numerical models of the geodynamo between epochs 2019.0 and 2025.0. The only difference between each ensemble member lies in the initial condition that is used for the numerical integration, all other control parameters being fixed. An initial condition is defined as follows: an estimate of the magnetic field and its rate-of-change at the core surface for 2019.0 is obtained from a year (2018.5–2019.5) of vector Swarm data. This estimate (common to all ensemble members) is subject to prior constraints: the statistical properties of the numerical dynamo model for the main geomagnetic field and its secular variation, and prescribed covariances for the other sources. One next considers 100 three-dimensional core states (in terms of flow, buoyancy and magnetic fields) extracted at different discrete times from a dynamo simulation that is not constrained by observations, with the time distance between each state exceeding the dynamo decorrelation time. Each state is adjusted (in three dimensions) in order to take the estimate of the geomagnetic field and its rate-of-change for 2019.0 into account. This methodology provides 100 different initial conditions for subsequent numerical integration of the dynamo model up to epoch 2025.0. Focussing on the 2020.0–2025.0 time window, we use the median average rate-of-change of each Gauss coefficient of the ensemble and its statistics to define the geomagnetic secular variation over that time frame and its uncertainties.https://doi.org/10.1186/s40623-020-01309-9Earth’s magnetic fieldGeomagnetic secular variationSatellite magneticsDynamo: theory and simulationInverse theory |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Alexandre Fournier Julien Aubert Vincent Lesur Guillaume Ropp |
spellingShingle |
Alexandre Fournier Julien Aubert Vincent Lesur Guillaume Ropp A secular variation candidate model for IGRF-13 based on Swarm data and ensemble inverse geodynamo modelling Earth, Planets and Space Earth’s magnetic field Geomagnetic secular variation Satellite magnetics Dynamo: theory and simulation Inverse theory |
author_facet |
Alexandre Fournier Julien Aubert Vincent Lesur Guillaume Ropp |
author_sort |
Alexandre Fournier |
title |
A secular variation candidate model for IGRF-13 based on Swarm data and ensemble inverse geodynamo modelling |
title_short |
A secular variation candidate model for IGRF-13 based on Swarm data and ensemble inverse geodynamo modelling |
title_full |
A secular variation candidate model for IGRF-13 based on Swarm data and ensemble inverse geodynamo modelling |
title_fullStr |
A secular variation candidate model for IGRF-13 based on Swarm data and ensemble inverse geodynamo modelling |
title_full_unstemmed |
A secular variation candidate model for IGRF-13 based on Swarm data and ensemble inverse geodynamo modelling |
title_sort |
secular variation candidate model for igrf-13 based on swarm data and ensemble inverse geodynamo modelling |
publisher |
SpringerOpen |
series |
Earth, Planets and Space |
issn |
1880-5981 |
publishDate |
2021-02-01 |
description |
Abstract This paper describes the design of a candidate secular variation model for the 13th generation of the International Geomagnetic Reference Field. This candidate is based upon the integration of an ensemble of 100 numerical models of the geodynamo between epochs 2019.0 and 2025.0. The only difference between each ensemble member lies in the initial condition that is used for the numerical integration, all other control parameters being fixed. An initial condition is defined as follows: an estimate of the magnetic field and its rate-of-change at the core surface for 2019.0 is obtained from a year (2018.5–2019.5) of vector Swarm data. This estimate (common to all ensemble members) is subject to prior constraints: the statistical properties of the numerical dynamo model for the main geomagnetic field and its secular variation, and prescribed covariances for the other sources. One next considers 100 three-dimensional core states (in terms of flow, buoyancy and magnetic fields) extracted at different discrete times from a dynamo simulation that is not constrained by observations, with the time distance between each state exceeding the dynamo decorrelation time. Each state is adjusted (in three dimensions) in order to take the estimate of the geomagnetic field and its rate-of-change for 2019.0 into account. This methodology provides 100 different initial conditions for subsequent numerical integration of the dynamo model up to epoch 2025.0. Focussing on the 2020.0–2025.0 time window, we use the median average rate-of-change of each Gauss coefficient of the ensemble and its statistics to define the geomagnetic secular variation over that time frame and its uncertainties. |
topic |
Earth’s magnetic field Geomagnetic secular variation Satellite magnetics Dynamo: theory and simulation Inverse theory |
url |
https://doi.org/10.1186/s40623-020-01309-9 |
work_keys_str_mv |
AT alexandrefournier asecularvariationcandidatemodelforigrf13basedonswarmdataandensembleinversegeodynamomodelling AT julienaubert asecularvariationcandidatemodelforigrf13basedonswarmdataandensembleinversegeodynamomodelling AT vincentlesur asecularvariationcandidatemodelforigrf13basedonswarmdataandensembleinversegeodynamomodelling AT guillaumeropp asecularvariationcandidatemodelforigrf13basedonswarmdataandensembleinversegeodynamomodelling AT alexandrefournier secularvariationcandidatemodelforigrf13basedonswarmdataandensembleinversegeodynamomodelling AT julienaubert secularvariationcandidatemodelforigrf13basedonswarmdataandensembleinversegeodynamomodelling AT vincentlesur secularvariationcandidatemodelforigrf13basedonswarmdataandensembleinversegeodynamomodelling AT guillaumeropp secularvariationcandidatemodelforigrf13basedonswarmdataandensembleinversegeodynamomodelling |
_version_ |
1724270078424252416 |