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.…
Author details: | Maximilian Arthus SchannerORCiDGND, Stefan MauerbergerORCiDGND, Monika KorteORCiDGND, Matthias HolschneiderORCiDGND |
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DOI: | https://doi.org/10.1029/2020JB021548 |
ISSN: | 2169-9313 |
ISSN: | 2169-9356 |
Title of parent work (English): | Journal of geophysical research : JGR ; an international quarterly. B, Solid earth |
Publisher: | American Geophysical Union |
Place of publishing: | Washington |
Publication type: | Article |
Language: | English |
Date of first publication: | 2021/07/06 |
Publication year: | 2021 |
Release date: | 2023/11/08 |
Volume: | 126 |
Issue: | 7 |
Article number: | e2020JB021548 |
Number of pages: | 22 |
Funding institution: | Deutsche Forschungsgemeinschaft (DFG) |
Funding number: | 388291411 |
Organizational units: | Mathematisch-Naturwissenschaftliche Fakultät / Institut für Mathematik |
DDC classification: | 5 Naturwissenschaften und Mathematik / 55 Geowissenschaften, Geologie / 550 Geowissenschaften |
Peer review: | Referiert |
License (German): | CC-BY - Namensnennung 4.0 International |