4.5 Article

Joint Inversion of Receiver Functions and Apparent Incidence Angles for Sparse Seismic Data

Journal

EARTH AND SPACE SCIENCE
Volume 8, Issue 10, Pages -

Publisher

AMER GEOPHYSICAL UNION
DOI: 10.1029/2021EA001733

Keywords

seismology; receiver functions; planets; crustal thickness; joint inversion; incidence angles

Funding

  1. IMPRS
  2. Emeritus group
  3. DLR German Space Agency
  4. Projekt DEAL

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Estimation of crustal structure and thickness is crucial for understanding planetary formation and evolution, particularly for planets like Mars with low seismic activity due to lack of plate tectonics. The proposed method of joint inversion of receiver functions and apparent incidence angles, along with information-theoretic statistical tests for model selection, can enhance accuracy in data analysis.
The estimation of crustal structure and thickness is essential in understanding the formation and evolution of terrestrial planets. Initial planetary missions with seismic instrumentation on board face the additional challenge of dealing with seismic activity levels that are only poorly constrained a priori. For example, the lack of plate tectonics on Mars leads to low seismicity, which could, in turn, hinder the application of many terrestrial data analysis techniques. Here we propose using a joint inversion of receiver functions and apparent incidence angles, which contain information on absolute S-wave velocities of the subsurface. Since receiver function inversions suffer from a velocity depth trade-off, we in addition exploit a simple relation that defines apparent S-wave velocity as a function of observed apparent P-wave incidence angles to constrain the parameter space. We then use the Neighborhood Algorithm for the inversion of a suitable joint objective function. The resulting ensemble of models is then used to derive uncertainty estimates for each model parameter. In preparation for the analysis of data from the InSight mission, we show the application of our proposed method on Mars synthetics and sparse terrestrial data sets from different geological settings using both single and multiple events. We use information-theoretic statistical tests as model selection criteria and discuss their relevance and implications in a seismological framework.

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