Data Publications

Supplement to “Synchronization of great subduction megathrust earthquakes: Insights from scale model analysis”

hasData_Center_Short_Name
  • Deutsches GeoForschungsZentrum GFZ
hasDataset_Online_Resource
hasDataset_Release_Date
  • 2019
hasDataset_Title
  • Supplement to “Synchronization of great subduction megathrust earthquakes: Insights from scale model analysis”
hasEntry_ID
  • 10.5880/GFZ.4.1.2019.005
hasKeyword
  • EPOS
  • multi-scale laboratories
  • European Plate Observing System
  • analogue modelling results
  • analogue models of geologic processes
  • software tools
  • Megathrust earthquakes
  • computational statistics
hasSummary
  • This data set provides data from subduction zone earthquake experiments and analysis described in Rosenau et al. (2019). In the experiments analogue seismotectonic scale models of subduction zones characterized by two seismogenic asperities are used to study the interaction of asperities over multiple seismic cycles by means of static (Coulomb failure) stress transfer. Various asperity geometries (lateral/along-strike of the subduction zone distance and vertical/across-strike of the subduction zone offset) are tested on their effect on recurrence pattern of simulated great (M8+) earthquakes. The results demonstrate the role of stress coupling in the synchronization of asperities leading to multi-asperity M9+ events in nature. The data set contains time series of experimental surface velocities from which analogue earthquakes are detected and classified into synchronized events and solo events. The latter are subcategorized into main events and aftershocks and into normal and thrust events. An analogue earthquake catalogue lists all categorized events of the 12 experiments used for statistical analysis. Moreover, results from elastic dislocation modelling aimed ate quantifying the stress coupling between the asperities for the various geometries are summarized. Basic statistics of classified events (e.g. percentage of categorized events, coefficient of variation in size and recurrence time etc.) are documented. Matlab scripts are provided to visualize the data as in the paper.
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