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Software

BEAT : Bayesian Earthquake Analysis Tool

Urheber*innen

Vasyura-Bathke,  Hannes
External Organizations;

Dettmer,  Jan
External Organizations;

/persons/resource/asteinbe

Steinberg,  Andreas
2.1 Physics of Earthquakes and Volcanoes, 2.0 Geophysics, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

/persons/resource/heimann

Heimann,  Sebastian
2.1 Physics of Earthquakes and Volcanoes, 2.0 Geophysics, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

/persons/resource/isken

Isken,  Marius Paul
2.1 Physics of Earthquakes and Volcanoes, 2.0 Geophysics, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

Zielke,  Olaf
External Organizations;

Mai,  Paul Martin
External Organizations;

/persons/resource/hsudhaus

Sudhaus,  H.
2.1 Physics of Earthquakes and Volcanoes, 2.0 Geophysics, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

Jónsson,  Sigurjón
External Organizations;

Externe Ressourcen
Es sind keine externen Ressourcen hinterlegt
Volltexte (frei zugänglich)
Es sind keine frei zugänglichen Volltexte in GFZpublic verfügbar
Ergänzendes Material (frei zugänglich)
Es sind keine frei zugänglichen Ergänzenden Materialien verfügbar
Zitation

Vasyura-Bathke, H., Dettmer, J., Steinberg, A., Heimann, S., Isken, M. P., Zielke, O., Mai, P. M., Sudhaus, H., Jónsson, S.(2019): BEAT: Bayesian Earthquake Analysis Tool, Potsdam : GFZ Data Services.
https://doi.org/10.5880/fidgeo.2019.024


Zitierlink: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5000161
Zusammenfassung
BEAT is an open-source software tool for the robust characterization of the temporal and spatial evolution of earthquake rupture processes. It uses kinematic rupture models that include low-parametric models like Moment Tensors but also complex high-parametric, finite-extent sources. In other words, BEAT allows studying earthquakes on a first-order level as points with location, size and mechanisms. In consecutive steps, the complexity of the source model may be increased by various details up to the potential to resolve rupture dimension, fault segmentation, slip-distribution and slip-history. The source model parameters and their uncertainties are estimated based on seismic waveforms, and/or geodetic observations like InSAR and GNSS data. Rapid forward modeling is enabled by using pre-computed Green's function databases, handled through the Pyrocko software library. Based on these, synthetic data are provided for arbitrary earthquake rupture models embedded in heterogeneous media. For an extensive exploration of the often high-dimensional model parameter space, BEAT offers a suite of sampling algorithms for high-standard Bayesian inference. The implementations of these sampling algorithms exploit the parallel architecture of modern computers for optimal performance. Finally, BEAT offers easy configuration and automatic visualization of relevant results. The software relies on functionality from PYROCKO (Heimann et al., 2017) and KITE (optionally, Isken et al., 2017).