Bayesian Inference of Local Paleosecular Variation from Sparse Paleomagnetic Data

We introduce a novel Bayesian method to construct local paleosecular variation (PSV) curves. By modeling the geomagnetic field as a Gaussian process, global models can be incorporated as informative prior distributions. Because we use Hamiltonian Mont

Authors

Maximilian Arthus Schanner (ORCID: https://orcid.org/0000-0002-0497-9231)
Lennart Vincent de Groot (ORCID: https://orcid.org/0000-0002-1151-5662)
Romy Meyer (ORCID: https://orcid.org/0000-0002-2171-0955)

Institutions

Utrecht University (NL)
GFZ Helmholtz Centre for Geosciences (DE)

Publication Details

Published: 2025-09-02
DOI: https://doi.org/10.22541/essoar.175678480.02803836/v1
Primary Topic: Geomagnetism and Paleomagnetism Studies
Type: article
Field-Weighted Citation Impact: 0.00

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article

Bayesian Inference of Local Paleosecular Variation from Sparse Paleomagnetic Data

Maximilian Arthus Schanner, Lennart Vincent de Groot, Romy Meyer

Sep 2, 2025

Geomagnetism and Paleomagnetism Studies

article

Bayesian Inference of Local Paleosecular Variation from Sparse Paleomagnetic Data

Maximilian Arthus Schanner, Lennart Vincent de Groot, Romy Meyer

September 2, 2025article en

Abstract

We introduce a novel Bayesian method to construct local paleosecular variation (PSV) curves. By modeling the geomagnetic field as a Gaussian process, global models can be incorporated as informative prior distributions. Because we use Hamiltonian Mont

Utrecht University (NL), GFZ Helmholtz Centre for Geosciences (DE)

Openalex Percentile: Top 80%

Geomagnetism and Paleomagnetism Studies

DOI Open Access PDF OpenAlex

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Bayesian Inference of Local Paleosecular Variation from Sparse Paleomagnetic Data — Maximilian Arthus Schanner, Lennart Vincent de Groot, et al. · (2025) | TGRS Research Map | TGRS