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An inquiry into the lunar interior: A nonlinear inversion of the Apollo lunar seismic data

This study discusses in detail the inversion of the Apollo lunar seismic data and the question of how to analyze the results. The well-known problem of estimating structural parameters (seismic velocities) and other parameters crucial to an understanding of a planetary body from a set of arrival...

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Main Authors: Adnan, Shahid Khan, Klaus, Mosegaard
Format: E-Article
Language:English
Published: American Geophysical Union. 2002
Subjects:
G Geography (General)
Online Access:http://ir.unimas.my/id/eprint/9774/1/An%20inquiry%20into%20the%20lunar%20interior%20A%20nonlinear%20inversion%20of%20the%20Apollo%20lunar%20seismic%20data%20%28abstract%29.pdf
http://ir.unimas.my/id/eprint/9774/
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spelling my.unimas.ir.97742015-11-18T08:14:59Z http://ir.unimas.my/id/eprint/9774/ An inquiry into the lunar interior: A nonlinear inversion of the Apollo lunar seismic data Adnan, Shahid Khan Klaus, Mosegaard G Geography (General) This study discusses in detail the inversion of the Apollo lunar seismic data and the question of how to analyze the results. The well-known problem of estimating structural parameters (seismic velocities) and other parameters crucial to an understanding of a planetary body from a set of arrival times is strongly nonlinear. Here we consider this problem from the point of view of Bayesian statistics using a Markov chain Monte Carlo method. Generally, the results seem to indicate a somewhat thinner crust with a thickness around 45 km as well as a more detailed lunar velocity structure, especially in the middle mantle, than obtained in earlier studies. Concerning the moonquake locations, the shallow moonquakes are found in the depth range 50–220 km, and the majority of deep moonquakes are concentrated in the depth range 850–1000 km, with what seems to be an apparently rather sharp lower boundary. In wanting to further analyze the outcome of the inversion for specific features in a statistical fashion, we have used credible intervals, twodimensional marginals, and Bayesian hypothesis testing. Using this form of hypothesis testing, we are able to decide between the relative importance of any two hypotheses given data, prior information, and the physical laws that govern the relationship between model and data, such as having to decide between a thin crust of 45 km and a thick crust as implied by the generally assumed value of 60 km. We obtain a Bayes factor of 4.2, implying that a thinner crust is strongly favored. American Geophysical Union. 2002 E-Article NonPeerReviewed text en http://ir.unimas.my/id/eprint/9774/1/An%20inquiry%20into%20the%20lunar%20interior%20A%20nonlinear%20inversion%20of%20the%20Apollo%20lunar%20seismic%20data%20%28abstract%29.pdf Adnan, Shahid Khan and Klaus, Mosegaard (2002) An inquiry into the lunar interior: A nonlinear inversion of the Apollo lunar seismic data. Journal Of Geophysical Research, 107 (E6). ISSN 0148-0227 DOI: 10.1029/2001JE001658
institution Universiti Malaysia Sarawak
building Centre for Academic Information Services (CAIS)
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sarawak
content_source UNIMAS Institutional Repository
url_provider http://ir.unimas.my/
language English
topic G Geography (General)
spellingShingle G Geography (General)
Adnan, Shahid Khan
Klaus, Mosegaard
An inquiry into the lunar interior: A nonlinear inversion of the Apollo lunar seismic data
description This study discusses in detail the inversion of the Apollo lunar seismic data and the question of how to analyze the results. The well-known problem of estimating structural parameters (seismic velocities) and other parameters crucial to an understanding of a planetary body from a set of arrival times is strongly nonlinear. Here we consider this problem from the point of view of Bayesian statistics using a Markov chain Monte Carlo method. Generally, the results seem to indicate a somewhat thinner crust with a thickness around 45 km as well as a more detailed lunar velocity structure, especially in the middle mantle, than obtained in earlier studies. Concerning the moonquake locations, the shallow moonquakes are found in the depth range 50–220 km, and the majority of deep moonquakes are concentrated in the depth range 850–1000 km, with what seems to be an apparently rather sharp lower boundary. In wanting to further analyze the outcome of the inversion for specific features in a statistical fashion, we have used credible intervals, twodimensional marginals, and Bayesian hypothesis testing. Using this form of hypothesis testing, we are able to decide between the relative importance of any two hypotheses given data, prior information, and the physical laws that govern the relationship between model and data, such as having to decide between a thin crust of 45 km and a thick crust as implied by the generally assumed value of 60 km. We obtain a Bayes factor of 4.2, implying that a thinner crust is strongly favored.
format E-Article
author Adnan, Shahid Khan
Klaus, Mosegaard
author_facet Adnan, Shahid Khan
Klaus, Mosegaard
author_sort Adnan, Shahid Khan
title An inquiry into the lunar interior: A nonlinear inversion of the Apollo lunar seismic data
title_short An inquiry into the lunar interior: A nonlinear inversion of the Apollo lunar seismic data
title_full An inquiry into the lunar interior: A nonlinear inversion of the Apollo lunar seismic data
title_fullStr An inquiry into the lunar interior: A nonlinear inversion of the Apollo lunar seismic data
title_full_unstemmed An inquiry into the lunar interior: A nonlinear inversion of the Apollo lunar seismic data
title_sort inquiry into the lunar interior: a nonlinear inversion of the apollo lunar seismic data
publisher American Geophysical Union.
publishDate 2002
url http://ir.unimas.my/id/eprint/9774/1/An%20inquiry%20into%20the%20lunar%20interior%20A%20nonlinear%20inversion%20of%20the%20Apollo%20lunar%20seismic%20data%20%28abstract%29.pdf
http://ir.unimas.my/id/eprint/9774/
_version_ 1644510806394535936
score 13.211869

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