PADM2M: a penalized maximum likelihood model of the 0–2 Ma palaeomagnetic axial dipole moment

By L. Ziegler, Catherine Constable, Catherine L. Johnson, Lisa Tauxe. 2011

179 citations recorded by the source corpus.

SUMMARY We present a new time-varying model for palaeomagnetic axial dipole moment (PADM) for the past 2 Myr and compare it with earlier virtual axial dipole moment (VADM) reconstructions which have been based on stacking and averaging scaled relative palaeointensity records. The PADM is derived from both absolute and relative palaeointensity data and constructed using a new penalized maximum likelihood (PML) approach to recover a cubic B-spline representation of axial-dipole field variations on million year timescales. The PML method is explicitly intended to reduce bias in estimating the true axial dipole moment that arises in average VADM reconstructions. We apply the PML method to a set of 96 032 published data (1800 palaeointensities from igneous rocks, 3300 archaeointensities and 86 relative palaeointensity time-series of variable lengths and resolutions). Two models are discussed: PADM2Mp is a trial model based on a subset of the nine longest available sedimentary records; PADM2M uses a comprehensive data set (76 records, 81 446 data; 10 records were eliminated) and is our preferred model. PADM2M has a lower mean than existing VADM reconstructions but shows similarities in long-period variability. Some differences in timing, amplitude and resolution of certain features can be attributed to variations in age assignments. Others result from our more comprehensive data set and a reduction in bias attributable to PML modelling. PADM2M has an average axial dipole moment over 0–2 Ma of 5.3 × 1022 Am2 with a standard deviation of 1.5 × 1022 Am2. The Brunhes chron average (6.2 × 1022 Am2) is higher than for earlier epochs of Matuyama (4.8 × 1022 Am2), as seen in some previous studies. The power spectrum for our model agrees with previous estimates of the global palaeomagnetic power spectrum for frequencies up to about 102 Myr−1. We see no distinctive evidence in the power spectrum for orbital forcing of geodynamo behaviour.

Subfields: Atmospheric Science, Geophysics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/81518381da261a5d12b641d963623881f1b34dc2

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The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atmospheric Science

1. Xiang Zhao
2. D. Heslop
3. G. Balco
4. A. Roberts
5. Lisa Tauxe
6. Zhaoxia Jiang
7. V. Laurent
8. L. Martin

In Geophysics

1. Xiang Zhao
2. A. Roberts
3. D. Heslop
4. Lisa Tauxe
5. G. Balco
6. N. Lifton
7. R. Egli
8. A. Biggin

In Molecular Biology

1. Xiang Zhao
2. D. Heslop
3. A. Roberts
4. G. Balco
5. Lisa Tauxe
6. Zhaoxia Jiang
7. N. Lifton
8. R. Egli

Citations in the corpus

• The CREp program and the ICE-D production rate calibration database: A fully parameterizable and updated online tool to compute cosmic-ray exposure ages (2017, methodology): “…framework including the Yang et al. (2000), Korte et al. (2005) and SINT800 (Guyodo and Valet, 1999) reconstructions, whereas the Lifton et al. (2014) LSD model uses CALS3k.3 (Korte et al., 2009), CALS7k.2 (Korte et al., 2005), GLOPIS-75 (Laj et al., 2004) and PADM2M (Ziegler et al., 2011).”
• A Critical Appraisal of the “Day” Diagram (2017, background): “Despite the excellent directional recording, the relative paleointensity signal extracted from this core does not agree well with global stacks (e.g., Valet et al., 2005; Ziegler et al., 2011) through the time period analyzed by Dinarès-Turell et al.”