Articles | Volume 7, issue 6
Research article
07 Nov 2016
Research article |  | 07 Nov 2016

Fully probabilistic seismic source inversion – Part 2: Modelling errors and station covariances

Simon C. Stähler and Karin Sigloch

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Cited articles

Bodin, T.: Transdimensional Approaches to Geophysical Inverse Problems, Ph.D. thesis, Australian National University, 2010.
Bodin, T., Sambridge, M., Rawlinson, N., and Arroucau, P.: Transdimensional tomography with unknown data noise, Geophys. J. Int., 189, 1536–1556,, 2012.
Bodin, T., Leiva, J., Romanowicz, B., Maupin, V., and Yuan, H.: Imaging anisotropic layering with Bayesian inversion of multiple data types, Geophys. J. Int., 206, 605–629,, 2016.
Bogert, B.: Correction of seismograms for the transfer function of the seismometer, Bull. Seismol. Soc. Am., 52, 781–792, 1962.
Bondár, I. and Storchak, D. A.: Improved location procedures at the International Seismological Centre, Geophys. J. Int., 186, 1220–1244,, 2011.
Short summary
Seismic source inversion is the method of inferring the spatial orientation of an earthquake source from seismic records. The results come with large uncertainties, which we try to estimate in a Bayesian approach. We propose an empirical relationship for the likelihood function based on a large dataset of deterministic solutions. This allows using the cross-correlation coefficient as a misfit criterion, which is better suited for waveform comparison than the popular root mean square or L2 norm.