4.3 Article

Constraining earthquake source inversions with GPS data: 1. Resolution-based removal of artifacts

Journal

Publisher

AMER GEOPHYSICAL UNION
DOI: 10.1029/2007JB005449

Keywords

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Funding

  1. James S. McDonnell Foundation [21002070]
  2. NSF [DMR-0606092]
  3. David and Lucile Packard Foundation
  4. USGS [06HQGR0046, 02HQAG0008]
  5. Fundacao para a Ciencia e Tecnologia (Portuguese Foundation for Science and Technology)
  6. National Science Foundation [EAR-0512000, EAR-0106924]
  7. Southern California Earthquake Center

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We present a resolution analysis of an inversion of GPS data from the 2004 M-w 6.0 Parkfield earthquake. This earthquake was recorded at thirteen 1-Hz GPS receivers, which provides for a truly coseismic data set that can be used to infer the static slip field. We find that the resolution of our inverted slip model is poor at depth and near the edges of the modeled fault plane that are far from GPS receivers. The spatial heterogeneity of the model resolution in the static field inversion leads to artifacts in poorly resolved areas of the fault plane. These artifacts look qualitatively similar to asperities commonly seen in the final slip models of earthquake source inversions, but in this inversion they are caused by a surplus of free parameters. The location of the artifacts depends on the station geometry and the assumed velocity structure. We demonstrate that a nonuniform gridding of model parameters on the fault can remove these artifacts from the inversion. We generate a nonuniform grid with a grid spacing that matches the local resolution length on the fault and show that it outperforms uniform grids, which either generate spurious structure in poorly resolved regions or lose recoverable information in well-resolved areas of the fault. In a synthetic test, the nonuniform grid correctly averages slip in poorly resolved areas of the fault while recovering small-scale structure near the surface. Finally, we present an inversion of the Parkfield GPS data set on the nonuniform grid and analyze the errors in the final model.

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