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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...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2018
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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 |
Sumario: | 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] |
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