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Correlation based time evolution of the archeomagnetic field

  • In a previous study, a new snapshot modeling concept for the archeomagnetic field was introduced (Mauerberger et al., 2020, ). By assuming a Gaussian process for the geomagnetic potential, a correlation-based algorithm was presented, which incorporates a closed-form spatial correlation function. This work extends the suggested modeling strategy to the temporal domain. A space-time correlation kernel is constructed from the tensor product of the closed-form spatial correlation kernel with a squared exponential kernel in time. Dating uncertainties are incorporated into the modeling concept using a noisy input Gaussian process. All but one modeling hyperparameters are marginalized, to reduce their influence on the outcome and to translate their variability to the posterior variance. The resulting distribution incorporates uncertainties related to dating, measurement and modeling process. Results from application to archeomagnetic data show less variation in the dipole than comparable models, but are in general agreement with previousIn a previous study, a new snapshot modeling concept for the archeomagnetic field was introduced (Mauerberger et al., 2020, ). By assuming a Gaussian process for the geomagnetic potential, a correlation-based algorithm was presented, which incorporates a closed-form spatial correlation function. This work extends the suggested modeling strategy to the temporal domain. A space-time correlation kernel is constructed from the tensor product of the closed-form spatial correlation kernel with a squared exponential kernel in time. Dating uncertainties are incorporated into the modeling concept using a noisy input Gaussian process. All but one modeling hyperparameters are marginalized, to reduce their influence on the outcome and to translate their variability to the posterior variance. The resulting distribution incorporates uncertainties related to dating, measurement and modeling process. Results from application to archeomagnetic data show less variation in the dipole than comparable models, but are in general agreement with previous findings.zeige mehrzeige weniger

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Metadaten
Verfasserangaben:Maximilian Arthus SchannerORCiDGND, Stefan MauerbergerORCiDGND, Monika KorteORCiDGND, Matthias HolschneiderORCiDGND
DOI:https://doi.org/10.1029/2020JB021548
ISSN:2169-9313
ISSN:2169-9356
Titel des übergeordneten Werks (Englisch):Journal of geophysical research : JGR ; an international quarterly. B, Solid earth
Verlag:American Geophysical Union
Verlagsort:Washington
Publikationstyp:Wissenschaftlicher Artikel
Sprache:Englisch
Datum der Erstveröffentlichung:06.07.2021
Erscheinungsjahr:2021
Datum der Freischaltung:08.11.2023
Band:126
Ausgabe:7
Aufsatznummer:e2020JB021548
Seitenanzahl:22
Fördernde Institution:Deutsche Forschungsgemeinschaft (DFG)
Fördernummer:388291411
Organisationseinheiten:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Mathematik
DDC-Klassifikation:5 Naturwissenschaften und Mathematik / 55 Geowissenschaften, Geologie / 550 Geowissenschaften
Peer Review:Referiert
Lizenz (Deutsch):License LogoCC-BY - Namensnennung 4.0 International
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