Simulating California Earthquakes

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Simulating California Earthquakes Using Virtual
California Contributions to the WGCEP
Donald Turcotte Professor of Geology University
of California, Davis Presented at WGCEP Meeting,
Lake Arrowhead, CA March 8, 2007
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Collaborators

• US Scientists
• Andrea Donnellan, Division of Earth and Space
  Science, JPL
• Geoffrey Fox, Dept. of Computer Science,
  University of Indiana
• Robert Granat ,Data Understanding Systems Group,
  JPL
• Lisa Grant, Dept. of Environmental Science,
  University of California, Irvine
• James Holliday, Dept. of Physics and CSE,
  University of California, Davis
• Peggy Li, Parallel Applications Technologies
  Group, JPL
• Bill Klein, Dept. of Physics, Boston Univ. and
  CNLS, LANL
• Greg Lyzenga, Dept. of Physics, Harvey Mudd
  College
• Jorge Martins, Universidad Fluminense, Niteroi,
  Brazil
• Dennis McLeod, Dept. of Computer Science, USC
• Gleb Yakovlev, CSE, University of California,
  Davis
• Kazuyoshi Nanjo, CSE, UC Davis and Tohoku
  University, Japan
• Jay Parker, Satellite Geodesy and Geodetic
  Systems, JPL
• Marlon Pierce, Community Grids Lab, University of
  Indiana
• Paul Rundle, Dept. of Physics and CSE, University
  of California, Davis
• Robert Shcherbakov, CSE, University of
  California, Davis
• Kristy Tiampo, Dept. of Earth Sciences,
  University of Western Ontario, London, Ontario
• Terry Tullis, Dept. of Geology, Brown University

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Recent Papers JB Rundle et al., A
simulation-based approach to forecasting the next
great San Francisco earthquake, Proc. Nat. Acad.
Sci., 102, 15363-15367 (2005). PB Rundle et al.,
Virtual California Fault model, frictional
parameters, applications, Pure. App. Geophys.,
163, 1819-1846 (2006). G Yakovlev et al.,
Simulation-based distributions of earthquake
recurrence times on the San Andreas fault system,
Bull. Seism. Soc. Am., 96, 1995-2007 (2006).
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Virtual California
Faults in RED are shown superposed on a LandSat
image of California. Geologic data are used to
set the model parameters. (Image courtesy of
Peggy Li, JPL)
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Virtual California
Backslip model Topology of fault system does
not evolve. Stress accumulation occurs as a
result of negative slip, or backslip. Linear
interactions (stress transfer) -- At the moment,
interactions are purely elastic, but
viscoelastic interactions can easily be
added. Arbitrarily complex 3D fault system
topologies -- At the moment, all faults are
vertical strike-slip faults. Boundary element
mesh is 10 km horizontal, 15 km vertical.
Faults are embedded in an elastic half space,
but layered media are possible as well.
Friction laws -- are static-dynamic with
additive stochastic noise. Rate-and- State
friction can be incorporated.
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Surface Deformation (Images Produced with Virtual
California code by P. Li, JPL)
Time Index 963
Time Index 190
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Synthetic earthquakes on the 132 elements of the
San Andreas fault 2000-year window from a
Virtual California simulation run of more than
1,000,000 yr
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Numerical Simulations Activity Through
Time Example Activity on the San Francisco
Segment of the San Andreas Fault
San Francisco Bay section of the San Andreas
fault is shown by the yellow fault line.
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Waiting Time Curves are Well Represented by the
Statistics of the Weibull Distribution as Shown
in the Figures Below
We compute (measure) Pm(to,t), which is the
conditional cumulative probability that an event
with magnitude M gt m will occur prior to a time t
from the present, given that it has not occurred
during the elapsed time to since the last event.
From this, we compute the median waiting time
until the next event, and the 25 - 75 envelope.
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Northern San Andreas, Mc 7.5, N 4606, ?
217.1 yrs, ? 114.7 yrs, Cv 0.528
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Northern San Andreas, Mc 7.5, N 4606, ?
217.1 yrs, ? 114.7 yrs, Cv 0.528
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Calaveras, Mc 6.8, N 8174, ? 122.3 yrs, ?
87.4 yrs, Cv 0.715
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Calaveras, Mc 6.8, N 8174, ? 122.3 yrs, ?
87.4 yrs, Cv 0.715
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Stress Dynamics and the Optimization of Numerical
Forecasts using Data-Scoring
Data Score
Time
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High and Low Scoring Events Virtual California -
Paleoseismology
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Comparison of Fault Topology in UCERF and in
Virtual California - 2006
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Virtual California New Features (Summer,
2007) Open source Object oriented coding (C,
Class structure) Dipping faults, arbitrary rake
angle New friction modules, including
rate-and-state friction Parallel implementation
in MPI-II Large data runs available on the web
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Summary According to the late K. Aki, we are
presently embarked on a new and exciting era of
earthquake forecasting research. The methods
used in weather and climate forecasting can be
adapted to earthquake forecasting as well (State
vectors, Principal Component Analysis, Numerical
simulations) Numerical simulations of complex
interacting multiscale fault systems are playing
an increasingly important role in understanding
earthquake physics and forecasting. Interactions
between faults play a critical role in organizing
the dynamics of the system Ensemble forecasting
will produce massive data sets due to the wide
variety of scales. InSAR data will play an
essential role, and will also produce massive
data sets whose analysis will provide a wealth of
information on earthquake physics
Major funding from NASA and US DoE Other funding
from South. Calif. EQ Center
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