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Predictions of the geomagnetic secular variation based on the ensemble sequential assimilation of geomagnetic field models by dynamo simulations

  • The IGRF offers an important incentive for testing algorithms predicting the Earth's magnetic field changes, known as secular variation (SV), in a 5-year range. Here, we present a SV candidate model for the 13th IGRF that stems from a sequential ensemble data assimilation approach (EnKF). The ensemble consists of a number of parallel-running 3D-dynamo simulations. The assimilated data are geomagnetic field snapshots covering the years 1840 to 2000 from the COV-OBS.x1 model and for 2001 to 2020 from the Kalmag model. A spectral covariance localization method, considering the couplings between spherical harmonics of the same equatorial symmetry and same azimuthal wave number, allows decreasing the ensemble size to about a 100 while maintaining the stability of the assimilation. The quality of 5-year predictions is tested for the past two decades. These tests show that the assimilation scheme is able to reconstruct the overall SV evolution. They also suggest that a better 5-year forecast is obtained keeping the SV constant compared toThe IGRF offers an important incentive for testing algorithms predicting the Earth's magnetic field changes, known as secular variation (SV), in a 5-year range. Here, we present a SV candidate model for the 13th IGRF that stems from a sequential ensemble data assimilation approach (EnKF). The ensemble consists of a number of parallel-running 3D-dynamo simulations. The assimilated data are geomagnetic field snapshots covering the years 1840 to 2000 from the COV-OBS.x1 model and for 2001 to 2020 from the Kalmag model. A spectral covariance localization method, considering the couplings between spherical harmonics of the same equatorial symmetry and same azimuthal wave number, allows decreasing the ensemble size to about a 100 while maintaining the stability of the assimilation. The quality of 5-year predictions is tested for the past two decades. These tests show that the assimilation scheme is able to reconstruct the overall SV evolution. They also suggest that a better 5-year forecast is obtained keeping the SV constant compared to the dynamically evolving SV. However, the quality of the dynamical forecast steadily improves over the full assimilation window (180 years). We therefore propose the instantaneous SV estimate for 2020 from our assimilation as a candidate model for the IGRF-13. The ensemble approach provides uncertainty estimates, which closely match the residual differences with respect to the IGRF-13. Longer term predictions for the evolution of the main magnetic field features over a 50-year range are also presented. We observe the further decrease of the axial dipole at a mean rate of 8 nT/year as well as a deepening and broadening of the South Atlantic Anomaly. The magnetic dip poles are seen to approach an eccentric dipole configuration.zeige mehrzeige weniger

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Metadaten
Verfasserangaben:Sabrina Sanchez, Johannes WichtORCiD, Julien BärenzungORCiD
DOI:https://doi.org/10.1186/s40623-020-01279-y
ISSN:1880-5981
Titel des übergeordneten Werks (Englisch):Earth, planets and space
Verlag:Springer
Verlagsort:New York
Publikationstyp:Wissenschaftlicher Artikel
Sprache:Englisch
Datum der Erstveröffentlichung:22.10.2020
Erscheinungsjahr:2020
Datum der Freischaltung:04.10.2022
Freies Schlagwort / Tag:Data assimilation; Dynamo; Earth's magnetic field; Geomagnetic secular variation; simulations
Band:72
Ausgabe:1
Aufsatznummer:157
Seitenanzahl:20
Fördernde Institution:German Research Foundation (DFG)German Research Foundation (DFG) [SPP; 1788]
Organisationseinheiten:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Mathematik
DDC-Klassifikation:5 Naturwissenschaften und Mathematik / 51 Mathematik / 510 Mathematik
Peer Review:Referiert
Publikationsweg:Open Access / Gold Open-Access
Lizenz (Deutsch):License LogoCC-BY - Namensnennung 4.0 International
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