Instrument response removal and the 2020 mlg 3.1 marlboro, new jersey, earthquake

Alexander L Burky*, Jessica C E Irving, Frederik J Simons

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

2 Citations (Scopus)
56 Downloads (Pure)


To better understand earthquakes as a hazard and to better understand the interior structure of the Earth, we often want to measure the physical displacement, velocity, or acceleration at locations on the Earth’s surface. To this end, a routine step in an observational seismology workflow is the removal of the instrument response, required to convert the digital counts recorded by a seismometer to physical displacement, velocity, or acceleration. The conceptual framework, which we briefly review for students and researchers of seismology, is that of the seismometer as a linear time‐invariant system, which records a convolution of ground motion via a transfer function that gain scales and phase shifts the incoming signal. In practice, numerous software packages are widely used to undo this convolution via deconvolution of the instrument’s transfer function. Here, to allow the reader to understand this process, we start by taking a step back to fully explore the choices made during this routine step and the reasons for making them. In addition, we introduce open‐source routines in Python and MATLAB as part of our rflexa package, which identically reproduce the results of the Seismic Analysis Code, a ubiquitous and trusted reference. The entire workflow is illustrated on data recorded by several instruments on Princeton University campus in Princeton, New Jersey, of the 9 September 2020 magnitude 3.1 earthquake in Marlboro, New Jersey.
Original languageEnglish
Pages (from-to)3865-3872
Number of pages8
JournalSeismological Research Letters
Issue number6
Early online date4 Aug 2021
Publication statusPublished - Nov 2021

Bibliographical note

Funding Information:
The authors thank the Incorporated Research Institutions for Seismology (IRIS) for providing the Seismic Analysis Code (SAC) software package (and its source code) to use as a reference for benchmarking our codes. Partial support for this work was provided by the National Science Foundation (NSF) under Grant Number EAR-1736046. The authors thank Lucas Sawade for providing access to the Raspberry Shake 3D data, and the authors also thank the Princeton Department of Geosciences, the High Meadows

Publisher Copyright:
© 2021 Seismological Society of America. All rights reserved.


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