Cargando…

Cross-validation of independent ultra-low-frequency magnetic recording systems for active fault studies

When working with ultra-low-frequency (ULF) magnetic datasets, as with most geophysical time-series data, it is important to be able to distinguish between cultural signals, internal instrument noise, and natural external signals with their induced telluric fields. This distinction is commonly attem...

Descripción completa

Detalles Bibliográficos
Autores principales: Wang, Can, Bin, Chen, Christman, Lilianna E., Glen, Jonathan M. G., Klemperer, Simon L., McPhee, Darcy K., Kappler, Karl N., Bleier, Tom E., Dunson, J. Clark
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6560705/
https://www.ncbi.nlm.nih.gov/pubmed/31258377
http://dx.doi.org/10.1186/s40623-018-0823-7
_version_ 1783425999966306304
author Wang, Can
Bin, Chen
Christman, Lilianna E.
Glen, Jonathan M. G.
Klemperer, Simon L.
McPhee, Darcy K.
Kappler, Karl N.
Bleier, Tom E.
Dunson, J. Clark
author_facet Wang, Can
Bin, Chen
Christman, Lilianna E.
Glen, Jonathan M. G.
Klemperer, Simon L.
McPhee, Darcy K.
Kappler, Karl N.
Bleier, Tom E.
Dunson, J. Clark
author_sort Wang, Can
collection PubMed
description When working with ultra-low-frequency (ULF) magnetic datasets, as with most geophysical time-series data, it is important to be able to distinguish between cultural signals, internal instrument noise, and natural external signals with their induced telluric fields. This distinction is commonly attempted using simultaneously recorded data from a spatially remote reference site. Here, instead, we compared data recorded by two systems with different instrumental characteristics at the same location over the same time period. We collocated two independent ULF magnetic systems, one from the QuakeFinder network and the other from the United States Geological Survey (USGS)-Stanford network, in order to cross-compare their data, characterize data reproducibility, and characterize signal origin. In addition, we used simultaneous measurements at a remote geomagnetic observatory to distinguish global atmospheric signals from local cultural signals. We demonstrated that the QuakeFinder and USGS-Stanford systems have excellent coherence, despite their different sensors and digitizers. Rare instances of isolated signals recorded by only one system or only one sensor indicate that caution is needed when attributing specific recorded signal features to specific origins. [Image: see text]
format Online
Article
Text
id pubmed-6560705
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher Springer Berlin Heidelberg
record_format MEDLINE/PubMed
spelling pubmed-65607052019-06-26 Cross-validation of independent ultra-low-frequency magnetic recording systems for active fault studies Wang, Can Bin, Chen Christman, Lilianna E. Glen, Jonathan M. G. Klemperer, Simon L. McPhee, Darcy K. Kappler, Karl N. Bleier, Tom E. Dunson, J. Clark Earth Planets Space Full Paper When working with ultra-low-frequency (ULF) magnetic datasets, as with most geophysical time-series data, it is important to be able to distinguish between cultural signals, internal instrument noise, and natural external signals with their induced telluric fields. This distinction is commonly attempted using simultaneously recorded data from a spatially remote reference site. Here, instead, we compared data recorded by two systems with different instrumental characteristics at the same location over the same time period. We collocated two independent ULF magnetic systems, one from the QuakeFinder network and the other from the United States Geological Survey (USGS)-Stanford network, in order to cross-compare their data, characterize data reproducibility, and characterize signal origin. In addition, we used simultaneous measurements at a remote geomagnetic observatory to distinguish global atmospheric signals from local cultural signals. We demonstrated that the QuakeFinder and USGS-Stanford systems have excellent coherence, despite their different sensors and digitizers. Rare instances of isolated signals recorded by only one system or only one sensor indicate that caution is needed when attributing specific recorded signal features to specific origins. [Image: see text] Springer Berlin Heidelberg 2018-04-18 2018 /pmc/articles/PMC6560705/ /pubmed/31258377 http://dx.doi.org/10.1186/s40623-018-0823-7 Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Full Paper
Wang, Can
Bin, Chen
Christman, Lilianna E.
Glen, Jonathan M. G.
Klemperer, Simon L.
McPhee, Darcy K.
Kappler, Karl N.
Bleier, Tom E.
Dunson, J. Clark
Cross-validation of independent ultra-low-frequency magnetic recording systems for active fault studies
title Cross-validation of independent ultra-low-frequency magnetic recording systems for active fault studies
title_full Cross-validation of independent ultra-low-frequency magnetic recording systems for active fault studies
title_fullStr Cross-validation of independent ultra-low-frequency magnetic recording systems for active fault studies
title_full_unstemmed Cross-validation of independent ultra-low-frequency magnetic recording systems for active fault studies
title_short Cross-validation of independent ultra-low-frequency magnetic recording systems for active fault studies
title_sort cross-validation of independent ultra-low-frequency magnetic recording systems for active fault studies
topic Full Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6560705/
https://www.ncbi.nlm.nih.gov/pubmed/31258377
http://dx.doi.org/10.1186/s40623-018-0823-7
work_keys_str_mv AT wangcan crossvalidationofindependentultralowfrequencymagneticrecordingsystemsforactivefaultstudies
AT binchen crossvalidationofindependentultralowfrequencymagneticrecordingsystemsforactivefaultstudies
AT christmanliliannae crossvalidationofindependentultralowfrequencymagneticrecordingsystemsforactivefaultstudies
AT glenjonathanmg crossvalidationofindependentultralowfrequencymagneticrecordingsystemsforactivefaultstudies
AT klemperersimonl crossvalidationofindependentultralowfrequencymagneticrecordingsystemsforactivefaultstudies
AT mcpheedarcyk crossvalidationofindependentultralowfrequencymagneticrecordingsystemsforactivefaultstudies
AT kapplerkarln crossvalidationofindependentultralowfrequencymagneticrecordingsystemsforactivefaultstudies
AT bleiertome crossvalidationofindependentultralowfrequencymagneticrecordingsystemsforactivefaultstudies
AT dunsonjclark crossvalidationofindependentultralowfrequencymagneticrecordingsystemsforactivefaultstudies