The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/20260932

Diab Montero, Hamed Ali; Li, Meng; van Dinther, Ylona; Vossepoel, Femke (2023): Data underlying the publication: Estimating the Occurrence of Slow Slip Events and Earthquakes with an Ensemble Kalman Filter. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/20260932.v1

Dataset

• Geophysics
• Earth Sciences

DATA ASSIMILATION, Earthquakes, Ensemble Kalman Filter (EnKF), Ensemble Kalman Filter Data Assimilation, rate-and-state friction, Slow-slip event

CC BY 4.0

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Hamed Ali Diab Montero , Meng Li, Ylona van Dinther, Femke Vossepoel

Time series from perfect model experiments of an Ensemble Kalman Filter over a 1D model producing slow-slip events and earthquakes. The observations are shear stress and velocity at a single location aqay from the fault. The time series include the evolution of the shear stress, velocity and state theta at the fault and at the observation location. The prior, perturbed observations and posterior of every analysis step of the data assimilation are provided.

• 2023-04-05 first online, published, posted

4TU.ResearchData

g-zipped HDF5 and JSON files

Estimating the Occurrence of Slow Slip Events and Earthquakes with an Ensemble Kalman Filter

• InFocus: An Integrated Approach to Estimating Fault Slip Occurrence (grant code Grant number: DEEP.NL.2018.037) [more info...] NWO (Nederlandse Organisatie voor Wetenschappelijk Onderzoek)

TU Delft, Faculty of Civil Engineering and Geosciences, Department of Geoscience and Engineering.
Utrecht University, Faculty of Geosciences.