pySCu: A new python code for analyzing remagnetizations directions by means of small circle utilities
Resumen: The Small Circle (SC) methods are founded upon two main starting hypotheses: (i) the analyzed sites were remagnetized contemporarily, acquiring the same paleomagnetic direction. (ii) The deviation of the acquired paleomagnetic signal from its original direction is only due to tilting around the bedding strike and therefore the remagnetization direction must be located on a small circle (SC) whose axis is the strike of bedding and contains the in situ paleomagnetic direction. Therefore, if we analyze several sites (with different bedding strikes) their SCs will intersect in the remagnetization direction. The SC methods have two applications: (1) the Small Circle Intersection (SCI) method is capable of providing adequate approximations to the expected paleomagnetic direction when dealing with synfolding remagnetizations. By comparing the SCI direction with that predicted from an apparent polar wander path, the (re)magnetization can be dated. (2) Once the remagnetization direction is known, the attitude of the beds (at each site) can be restored to the moment of the acquisition of the remagnetization, showing a palinspastic reconstructuion of the structure. Some caveats are necessary under more complex tectonic scenarios, in which SC-based methods can lead to erroneous interpretations. However, the graphical output of the methods tries to avoid ‘black-box’ effects and can minimize misleading interpretations or even help, for example, to identify local or regional vertical axis rotations. In any case, the methods must be used with caution and always considering the knowledge of the tectonic frame. In this paper, some utilities for SCs analysis are automatized by means of a new Python code and a new technique for defining the uncertainty of the solution is proposed. With pySCu the SCs methods can be easily and quickly applied, obtaining firstly a set of text files containing all calculated information and subsequently generating a graphical output on the fly.
Idioma: Inglés
DOI: 10.1016/j.cageo.2017.07.002
Año: 2017
Publicado en: COMPUTERS & GEOSCIENCES 109 (2017), 32-42 [45 pp.]
ISSN: 0098-3004

Factor impacto JCR: 2.567 (2017)
Categ. JCR: GEOSCIENCES, MULTIDISCIPLINARY rank: 62 / 189 = 0.328 (2017) - Q2 - T1
Categ. JCR: COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS rank: 37 / 105 = 0.352 (2017) - Q2 - T2

Factor impacto SCIMAGO: 1.35 - Information Systems (Q1) - Computers in Earth Sciences (Q1)

Financiación: info:eu-repo/grantAgreement/ES/MINECO/BES-2013-062988
Financiación: info:eu-repo/grantAgreement/ES/MINECO/CGL2012-38481
Financiación: info:eu-repo/grantAgreement/ES/MINECO/CGL2016-77560
Tipo y forma: Article (PostPrint)
Área (Departamento): Área Geodinámica Interna (Dpto. Ciencias de la Tierra)

Creative Commons You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. You may not use the material for commercial purposes. If you remix, transform, or build upon the material, you may not distribute the modified material.


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