AstroComb(v.1.0): non-linear, multi-channel, probabilistic cyclostratigraphic analysis

Abstract. We present a new algorithm for constructing floating astronomical timescales with explicit uncertainty estimates from sedimentary sequences. The method integrates probabilistic spectral analysis with inverse geochronological modeling, applied to ultra-high-resolution, multiproxy datasets such as core scanning X-Ray Fluorescence (XRF) elemental records. Our framework does not smooth data or impose layer-to-layer dependency, allowing sedimentation rates to vary abruptly at short stratigraphic length scales. By detecting and statistically constraining Milankovitch cycles preserved in stratigraphic signals, the algorithm seeks a floating age-depth model that can be anchored to astronomical tie points, where available. The resulting timescales enable precise, uncertainty-bounded timing of biostratigraphic zones, geochemical events, and depositional cycles. This approach advances astrochronology by combining cycle detection with formal stratigraphic modelling, while preserving fine-scale depositional variability, offering a reproducible and statistically rigorous framework for dating deep-time records.

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Publication Details

Journal
Geoscientific model development
Published
2026-10-26
DOI
https://doi.org/10.5194/gmd-19-10143-2026
Primary Topic
Geology and Paleoclimatology Research
Type
article
Field-Weighted Citation Impact
0.00

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AstroComb(v.1.0): non-linear, multi-channel, probabilistic cyclostratigraphic analysis

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2 links
Geoscientific model development
Geology and Paleoclimatology Research
article

AstroComb(v.1.0): non-linear, multi-channel, probabilistic cyclostratigraphic analysis

Mohammad Youssof, Klaus Mosegaard, Nicolas Rudolph Thibault, Tais W. Dahl, Aske Lohse Sørensen, Iris Fernandes
article en

Abstract

Abstract. We present a new algorithm for constructing floating astronomical timescales with explicit uncertainty estimates from sedimentary sequences. The method integrates probabilistic spectral analysis with inverse geochronological modeling, applied to ultra-high-resolution, multiproxy datasets such as core scanning X-Ray Fluorescence (XRF) elemental records. Our framework does not smooth data or impose layer-to-layer dependency, allowing sedimentation rates to vary abruptly at short stratigraphic length scales. By detecting and statistically constraining Milankovitch cycles preserved in stratigraphic signals, the algorithm seeks a floating age-depth model that can be anchored to astronomical tie points, where available. The resulting timescales enable precise, uncertainty-bounded timing of biostratigraphic zones, geochemical events, and depositional cycles. This approach advances astrochronology by combining cycle detection with formal stratigraphic modelling, while preserving fine-scale depositional variability, offering a reproducible and statistically rigorous framework for dating deep-time records.

Geoscientific model developmentVol. 19(20)
University of Copenhagen (DK)
Villum Fonden
Openalex Percentile: Top 89%
Geology and Paleoclimatology Research
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