Articles | Volume 11, issue 4
Method article
28 Aug 2020
Method article |  | 28 Aug 2020

Introducing noisi: a Python tool for ambient noise cross-correlation modeling and noise source inversion

Laura Ermert, Jonas Igel, Korbinian Sager, Eléonore Stutzmann, Tarje Nissen-Meyer, and Andreas Fichtner


Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Laura Ermert on behalf of the Authors (25 Jun 2020)  Author's response   Manuscript 
ED: Publish as is (03 Jul 2020) by Michal Malinowski
ED: Publish as is (05 Jul 2020) by CharLotte Krawczyk (Executive editor)
AR by Laura Ermert on behalf of the Authors (07 Jul 2020)  Author's response   Manuscript 
Short summary
We present an open-source tool to model ambient seismic auto- and cross-correlations with spatially varying source spectra. The modeling is based on pre-computed databases of seismic wave propagation, which can be obtained from public data providers. The aim of this tool is to facilitate the modeling of ambient noise correlations, which are an important seismologic observable, with realistic wave propagation physics. We present a description and benchmark along with example use cases.