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Abstract We examine the behavior of natural basaltic and trachytic samples during paleointensity experiments on both the original and laboratory‐acquired thermal remanences and characterize the samples using proxies for domain state including curvature (k) and the bulk domain stability parameters of Paterson (2011,https://doi.org/10.1029/2011JB008369) and Paterson et al. (2017,https://doi.org/10.1073/pnas.1714047114), respectively. A curvature value of 0.164 (suggested by Paterson, 2011,https://doi.org/10.1029/2011JB008369) as a critical threshold that separates single‐domain‐like remanences from multidomain‐like remanances on the original paleointensity data was used to separate samples into “straight” (single‐domain‐like) and “curved” (multidomain‐like) groups. Specimens from the two sample sets were given a “fresh” thermal remanent magnetization in a 70 μT field and subjected to an infield‐zerofield, zerofield‐infield (IZZI)‐type (Yu et al., 2004,https://doi.org/10.1029/2003GC000630) paleointensity experiment. The straight sample set recovered the laboratory field with high precision while the curved set had much more scattered results (70.5 ± 1.5 and 71.9 ± 5.2 μT, respectively). The average intensity of both sets for straight and curved was quite close to the laboratory field of 70 μT, however, suggesting that if experiments contain a sufficient number of specimens, there does not seem to be a large bias in the field estimate. We found that the dependence of the laboratory thermal remanent magnetization on cooling rate was significant in most samples and did not depend on domain states inferred from proxies based on hysteresis measurements and should be estimated for all samples whose cooling rates differ from that used in the laboratory.
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Assessing Paleosecular Variation Averaging and Correcting Paleomagnetic Inclination Shallowing
Abstract This paper addresses one of the critical questions of scientific inquiry: How do we know when a given data set is representative of the phenomenon being examined? For paleomagnetists, the question is often whether a particular data set sufficiently averaged paleosecular variation (PSV). To this aim, we updated an existing PSV data set that now comprises 2,441 site mean directions from 94 individual studies (PSV10‐24). Minimal filtering for data quality resulted in 1,619 sites from 90 publications. Fitting PSV10‐24 with two newly defined parameters as well as two existing ones form the basis of a Giant Gaussian Process field model (THG24) consistent with the data. Drawing directions from THG24 yields directional distributions predicted for a given latitude allowing a comparison between empirical distributions and the cumulative distribution function generated by the model. This tests whether the observed data adequately averaged out PSV according to THG24. We applied these tests to five data sets from Large Igneous Provinces from the last billion years and find that they are consistent with the THG24 model as well. Sedimentary data sets that may have experienced inclination shallowing can be corrected using an (un)flattening factor that yields directions satisfying THG24 in a newly‐defined, four‐parameter space. This approach builds on the Elongation‐Inclination (E/I) method of Tauxe and Kent (2004),https://doi.org/10.1029/145gm08, so the approach introduced here is called SVEI. We show examples of the use of SVEI and explain how to use this newly developed Python code that is publicly available in the PmagPy GitHub repository.
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- PAR ID:
- 10532882
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Journal of Geophysical Research: Solid Earth
- Volume:
- 129
- Issue:
- 8
- ISSN:
- 2169-9313
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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