Geomagnetic field models covering past millennia rely on two main data sources: archaeomagnetic data, that provide snapshots of the geomagnetic field at specific locations, and sediment records, that deliver time series of the geomagnetic field from individual drill cores. The limited temporal and spatial global coverage with archaeomagnetic data necessitates use of sediment data, especially when models go further back in time. However, the accurate preprocessing and interpretation of sediment data is crucial. Unlike archaeomagnetic data, sediment data does not provide absolute values for intensities and declinations; instead, it represents relative variations. The detrital remanent magnetization (DRM) of sediment records is influenced by various depositional (dDRM) effects that can result in inclination shallowing, as well as post-depositional (pDRM) processes that cause a delayed and smoothed signal. To address the distortion associated with the pDRM effects, a novel class of flexible parameterized lock-in functions has been proposed. These lock-in functions involve four parameters, which are estimated using a Bayesian modeling technique and archaeomagnetic data. By extending the space of hyperparameters to include the calibration factor for intensities, the declination offsets and the inclination shallowing factor, we present a fully Bayesian preprocessing method for sediment records in form of a Python package, called extit{sedprep}. By applying the estimated parameters to the raw sediment data extit{sedprep} is able to provide a calibrated and preprocessed palaeomagnetic record.

A document by Lukas Bohsung. Click on the document to view its contents.

The primary data sources for reconstructing the geomagnetic field of the past millennia are archaeomagnetic and sedimentary paleomagnetic data. Sediment records, in particular, are crucial in extending the temporal and spatial coverage of global geomagnetic field models, especially when archaeomagnetic data is sparse. However, the post-depositional detrital remanent magnetization (pDRM) process is still poorly understood and can cause smoothing of the magnetic signal and offsets with respect to the sediment age. To make effective use of sedimentary data, it is essential to understand the lock-in process and its impact on the magnetic signal. In this study, we investigate the lock-in process theoretically and derive a parameterized lock-in function that can approximate possible lock-in behaviors. Additionally, we demonstrate that a lock-in function that is independent of absolute parameters can only be applied to the magnetic direction components (declination and inclination), but not to the relative intensity. Integrating this lock-in function into the ArchKalmag14k modeling procedure \cite{schanner2022archkalmag14k} allows including data from sediment records. The parameters of the lock-in function are estimated by the maximum likelihood method using archaeomagnetic data as a reference. The effectiveness of the proposed method is evaluated through synthetic tests. Additionally, we apply our technique to sediment records from two lakes in Sweden (Kälksjön and Gyltigesjön) as first case studies. Our results demonstrate that the proposed method is capable of effectively correcting the distortion caused by the lock-in process, making data from sedimentary records a more reliable and informative source for geomagnetic field reconstructions.