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

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Cited articles

Afanasiev, M., Boehm, C., van Driel, M., Krischer, L., Rietmann, M., May, D. A., Knepley, M. G., and Fichtner, A.: Modular and flexible spectral-element waveform modelling in two and three dimensions, Geophys. J. Int., 216, 1675–1692,, 2018. a
Aki, K.: Space and time spectra of stationary stochastic waves, with special reference to microtremors, B. Earthq. Res. I. Tokyo, 35, 415–456, 1957. a
Aki, K. and Richards, P.: Quantitative Seismology, University Science Books, Mill Valley, California, 2002. a, b
Ardhuin, F., Stutzmann, E., Schimmel, M., and Mangeney, A.: Ocean wave sources of seismic noise, J. Geophys. Res., 116, C09004,, 2011. a
Ardhuin, F., Gualtieri, L., and Stutzmann, E.: How ocean waves rock the Earth: Two mechanisms explain microseisms with periods 3 to 300 s, Geophys. Res. Lett., 42, 765–772,, 2015. a, b, c
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.