Emmy-Noether-Project "Bridging Geodesy and Seismology"

rigorously propagate data errors in our analyses and development of modelling standards for first-order earthquake source parameters

Model ensembles of Bayesian models
Bayesian ensembles of model parameters (black dots) and optimum model solutions of different source studies.H. Sudhaus

Results of our data analyses are never perfect. When we measure far traveling seismic waves at globally distributed stations, we often have noise at the locality of the seismic station which is introducing data errors.

The solid earth through which the seismic waves travel, is known to us only to some extent and we make errors in modelling wave travel times and the surface displacement. Further more are the assumptions we make on the shape of the earthquake rupture (e.g. planar rupture) only valid to some extent.

In other words, we have imperfect data, imperfect knowledge of the medium, which is rupturing and how it ruptures and so we can have only imperfect earthquake source models.

A very important part of our earthquake research is therefore to estimate how imperfect the models, how uncertain they can be as a quality measure of the results. Admitting uncertainty and efforts to estimate them as realistically as possible will render our results also more useful to their further use in science: geologic interpretation, hazard assessments and earthquake simulations.

This topic is an overarching one and of course important for all the project topics and cooperations, particularly for the cooperation the SRCMOD project and our KAUST partners and the IASPEI seismic moment tensor group.


SRCMOD Database