10.5880/fidgeo.2019.024 eng dataset GFZ German Research Centre for Geosciences datapub@gfz-potsdam.de http://www.gfz-potsdam.de Helmholtz-Centre Potsdam - GFZ German Research Centre for Geosciences Helmholtz-Centre Potsdam - GFZ German Research Centre for Geosciences pointOfContact 2019-09-28 urn:ogc:def:crs:EPSG:4326 BEAT - Bayesian Earthquake Analysis Tool 2019-09-28 revision doi:10.5880/fidgeo.2019.024 Vasyura-Bathke, Hannes University of Potsdam, Potsdam, Germany author Dettmer, Jan University of Calgary, Calgary, Canada author Steinberg, Andreas Christian-Albrechts-Universität zu Kiel , Kiel, Germany University author Heimann, Sebastian GFZ German Research Centre for Geosciences, Potsdam, Germany author Isken, Marius GFZ German Research Centre for Geosciences, Potsdam, Germany author Zielke, Olaf KAUST King Abdullah University of Science and Technology, Thuwal, Saudi Arabia author Mai, Paul Martin KAUST King Abdullah University of Science and Technology, Thuwal, Saudi Arabia author Sudhaus, Henriette Christian-Albrechts-Universität zu Kiel , Kiel, Germany University author Jónsson, Sigurjón KAUST King Abdullah University of Science and Technology, Thuwal, Saudi Arabia author GFZ Data Services publisher 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). Complete Vasyura-Bathke, Hannes University of Potsdam, Potsdam, Germany hvasbath@uni-potsdam.de pointOfContact Steinberg, Andreas Christian-Albrechts-Universität zu Kiel , Kiel, Germany University steinberg@geophyisk.uni-kiel.de pointOfContact Seismological geodetic software Python framework Earthquake source parameter estimation Bayesian Inference Uncertainty Quantification Finite Fault Inversion EARTH SCIENCE > HUMAN DIMENSIONS > NATURAL HAZARDS > EARTHQUAKES EARTH SCIENCE > SOLID EARTH > TECTONICS > PLATE TECTONICS EARTH SCIENCE > SOLID EARTH > TECTONICS > PLATE TECTONICS > STRAIN EARTH SCIENCE > SOLID EARTH > TECTONICS > VOLCANIC ACTIVITY NASA/GCMD Earth Science Keywords publication GNU General Public License, Version 3, 29 June 2007, Copyright © 2019 Hannes Vasyura-Bathke, University of Potsdam, Germany GNU General Public License, Version 3, 29 June 2007, Copyright © 2019 Hannes Vasyura-Bathke, University of Potsdam, Germany 10.5880/GFZ.2.1.2017.001 DOI References 10.5880/GFZ.2.1.2017.002 DOI References https://pyrocko.org/ URL References eng geoscientificInformation http://doi.org/10.5880/fidgeo.2019.024 WWW:LINK-1.0-http--link Data Access - DOI Data Access - DOI information