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dc.date.accessioned2024-03-08T16:23:06Z
dc.date.available2024-03-08T16:23:06Z
dc.date.created2023-11-07T11:06:16Z
dc.date.issued2023
dc.identifier.citationSapienza, F. Gallo, Leandro Cesar Zhang, Yiming Vaes, Bram Domeier, Mathew Michael Swanson-Hysell, Nicholas L. . Quantitative Analysis of Paleomagnetic Sampling Strategies. Journal of Geophysical Research (JGR): Solid Earth. 2023, 128(11)
dc.identifier.urihttp://hdl.handle.net/10852/109290
dc.description.abstractAbstract Sampling strategies used in paleomagnetic studies play a crucial role in dictating the accuracy of our estimates of properties of the ancient geomagnetic field. However, there has been little quantitative analysis of optimal paleomagnetic sampling strategies and the community has instead defaulted to traditional practices that vary between laboratories. In this paper, we quantitatively evaluate the accuracy of alternative paleomagnetic sampling strategies through numerical experiments and an associated analytical framework. Our findings demonstrate a strong correspondence between the accuracy of an estimated paleopole position and the number of sites or independent readings of the time‐varying paleomagnetic field, whereas larger numbers of in‐site samples have a dwindling effect. This remains true even when a large proportion of the sample directions are spurious. This approach can be readily achieved in sedimentary sequences by distributing samples stratigraphically, considering each sample as an individual site. However, where the number of potential independent sites is inherently limited the collection of additional in‐site samples can improve the accuracy of the paleopole estimate (although with diminishing returns with increasing samples per site). Where an estimate of the magnitude of paleosecular variation is sought, multiple in‐site samples should be taken, but the optimal number is dependent on the expected fraction of outliers. The use of filters based on angular distance helps the accuracy of paleopole estimation, but leads to inaccurate estimates of paleosecular variation. We provide both analytical formulas and a series of interactive Jupyter notebooks allowing optimal sampling strategies to be developed from user‐informed expectations.
dc.languageEN
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleQuantitative Analysis of Paleomagnetic Sampling Strategies
dc.title.alternativeENEngelskEnglishQuantitative Analysis of Paleomagnetic Sampling Strategies
dc.typeJournal article
dc.creator.authorSapienza, F.
dc.creator.authorGallo, Leandro Cesar
dc.creator.authorZhang, Yiming
dc.creator.authorVaes, Bram
dc.creator.authorDomeier, Mathew Michael
dc.creator.authorSwanson-Hysell, Nicholas L.
cristin.unitcode185,15,22,91
cristin.unitnameSenter for planetær beboelighet
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode2
dc.identifier.cristin2193127
dc.identifier.bibliographiccitationinfo:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Journal of Geophysical Research (JGR): Solid Earth&rft.volume=128&rft.spage=&rft.date=2023
dc.identifier.jtitleJournal of Geophysical Research (JGR): Solid Earth
dc.identifier.volume128
dc.identifier.issue11
dc.identifier.pagecount16
dc.identifier.doihttps://doi.org/10.1029/2023JB027211
dc.type.documentTidsskriftartikkel
dc.type.peerreviewedPeer reviewed
dc.source.issn2169-9313
dc.type.versionPublishedVersion
cristin.articleide2023JB02


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