Emmy-Noether-Project "Bridging Geodesy and Seismology"

Our group members at the Hack.
Impressions from the first BridGeS pyrocko hack weekFotos: H. Sudhaus



In the Summer 2016 we had our first group Kick-Off Hack Week at GFZ Potsdam. The BridGeS group had started to form with the fresh Msc Geophysics Andreas Steinberg as PhD and Msc Geophysics Marius Isken as our second software developer. These new members together with long-time colleagues Hannes, Sebastian and Henriette are discussing the state-of-the-art of our software analysis tools. In one room, for a whole week, with many snacks and litres of Mate softdrinks. Can this be the preferred 'project retreat' format for our project?

In this week the main goals have been to bring everyone on a good common information level, to outline and agree on the goals in the to-be-developed new modelling techniques combining InSAR data and seismological data, and a first listing of software tool requirements. Pyrocko so far is a seismology toolbox and needs to learn working with static displacements.

Participants (in order of appearance in the foto collage): Andreas Steinberg (CAU), Hannes Vasyura-Bathke (KAUST), Marius Isken (CAU), Sebastian Heimann (GFZ), also Marius Kriegerowski and Henriette Sudhaus


Ideas and products of the week in some more details

The forward-side of things:

  • Source models: We optionally enable a rectangular finite source model that is defined by uniform slip instead of uniform moment. Things to do are i) to revive the Eikonal source and ii) enable edge-slip-tapering, e.g. from a uniform stress-drop assumption
  • Targets: For the InSAR displacements we need a new type of target that is static, has the five pyrocko coordinates, has a time frame attribute, SAR line-of-sight angle information and data error variance-covariance information. To prepare and handle InSAR targets we want an in-house modul for basic visualization and target preparation (filtering, subsampling, etc).
  • Green's function store: We want to implement new Green's function methods for the static data bases for layered media. THE candidate is R. Wang's PSGRN.
  • Engine: Our engine to compile dynamic and static synthetic displacements needs to learn new static targets. Also, it needs to be more efficient to make things fast.

The backward-side (inverse) of things:

  • Misfit function: We want to have data error covariance for the seismic trace as well. We test robust and fast ways to get pre-event noise statistics.
  • Sampler: Sebastian introduces Grond and we all agree that the concept is very promising and that we want to further develop it. We want to make it Bayesian.



SRCMOD Database