Web Services Approach to Earthquake Physics

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Web Services Approach to Earthquake Physics

• Andrea Donnellan, NASA/JPL
• ACES Working Group Meeting, Brisbane
• June 5, 2003

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Key Questions

• What is the nature of deformation at plate
  boundaries and the implications for earthquake
  hazards?
• How is the land surface changing and producing
  natural hazards?
• What are the interactions among ice masses,
  oceans, and the solid earth and their
  implications for sea level change?
• How do magmatic systems evolve and under what
  conditions do volcanoes erupt?
• What are the dynamics of the mantle and crust and
  how does the earths surface respond?
• What are the dynamics of the earths magnetic
  field and its interactions with the earth system?

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The Solid Earth isComplex, Nonlinear, and
Self-Organizing

• Computational technologies can help answer these
  questions
• How can the study of strongly correlated solid
  earth systems be enabled by space-based data
  sets?
• What can numerical simulations reveal about the
  physical processes that characterize these
  systems?
• How do interactions in these systems lead to
  space-time correlations and patterns?
• What are the important feedback loops that
  mode-lock the system behavior?
• How do processes on a multiplicity of different
  scales interact to produce the emergent
  structures that are observed?
• Do the strong correlations allow the capability
  to forecast the system behavior in any sense?

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2002 NASA Computational Technologies Workshop
Recommendations

• Create a Solid Earth Research Virtual Observatory
  (SERVO)
• Numerous distributed heterogeneous real-time
  datasets
• Seamless access to large distributed volumes of
  data
• Data handling and archiving part of framework
• Tools for visualization, datamining, pattern
  recognition, and data fusion
• Develop an Solid Earth Science Problem Solving
  Environment (PSE)
• Addresses the NASA specific challenges of
  multiscale modeling
• Model and algorithm development and testing,
  visualization, and data assimilation
• Scalable to workstations or supercomputer
  depending on size of problem
• Numerical libraries existing within a compatible
  framework
• Improve the Computational Environment
• PetaFLOP computers with Terabytes of RAM
• Distributed and cluster computers for
  decomposable problems
• Development of GRID technologies

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Geodetic Strain Rates
Courtesy Steve Ward
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Stress is Transferred Between Faults
Subsequent earthquakes occur in regions of
increased stress.
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InSAR Image of the Hector Mine Event
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Hector Mine Earthquake Displacements
Courtesy Jay Parker and Ken Hurst
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How Do Faults Interact?The October 1999 Hector
Mine Earthquake

• The Magnitude 7.1 Hector Mine event (right)
  occurred about 7 years after the Magnitude 7.4
  Landers event (left) in Californias Mojave
  desert
• We know that they must be physically related to
  each other, and to the rest of the faults in
  southern California, but how?

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InSAR is One Key to Unlocking Earthquake Secrets
A modeled interferogram from the Northridge
earthquake showing how InSAR could map surface
deformation.
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Northridge was Observed with Synthetic Aperture
Radar
19931995 Interferogram
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Postseismic Motion was also Observable with InSAR
Postseismic Interferogram
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Post-Northridge Vertical Motions
Uplift Profile
Station Uplift

• The mountains grew an additional 12 cm in the two
  years following the earthquake.
• Consistent with fault afterslip.
• Not consistent with lower crustal relaxation.

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Results from Data Inversion Show Fault Afterslip
as Primary Mechanism

• Are neighboring faults being loaded?
• Afterslip on the main fault has slowed
  substantially.
• Lateral motion has not slowed down.

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Map View of Inversion Results
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Northridge Postseismic Modeled as Afterslip
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Anomalous Motion at JPL was Observed Related to
the Northridge Earthquake
Sierra Madre Fault

• This was the first time that long range
  interactions were observed.
• The earthquake probably triggered shallow slip on
  the Sierra Madre Fault.

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Fault Failure
Courtesy Terry Tullis
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California 3D Fault Simulations
Faults are shown as light lines, the earthquakes
at model year 4526 are shown as dark
lines Simulations indicate that major events are
clustered in time like the real
events. Simulations using a realistic
heterogeneous earth structure are computationally
intensive.
Courtesy Paul Rundle and John Rundle Submitted to
Physical Review Letters
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Modeling Faults as Interacting Systems
Garlock Fault
San Andreas Fault
Santa Cruz Island Fault
Santa Monica Fault
Landers Fault
Pisgah Fault
Palos Verdes Fault
San Jacinto Fault
Elsinore Fault
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Earthquakes on One Fault May Turn Earthquakes On
or Off on other Faults
Space-time Stress Diagram
Southern California Seismicity
Faults
Courtesy John Rundle
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Fault Interaction Simulation
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InSAR and Seismic Anomalies May Show Locations of
Future Earthquakes
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Space-Based Methods are Showing an Increasing
Number of Slow Events

• Slow earthquakes are observed in Cascadia and
  Japan along the subduction zones.
• In Canada, these events take about 15 days,
  propagate northward, and occur every 16-18 months.

August 1999 Transient Displacements Versus Long
Term Velocities
Courtesy Herb Dragert, Natural Resources, Canada
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Slip Occurs on the Deep Part of the Subduction
Zone
Courtesy Herb Dragert, Natural Resources, Canada
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Periodic Slow Earthquakes in Cascadia
Courtesy Herb Dragert, Natural Resources, Canada
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Computational Approach

• Modeling and Simulation Integrate multiple
  scales into computer simulations.
• Web services Simplified access to data,
  simulation codes, and flow between simulations of
  varying types.

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Current and Future Directions

• 1. Create a Solid Earth Research Virtual
  Observatory (SERVO)
• Incorporate numerous distributed heterogeneous
  real-time datasets
• Create seamless access to large distributed
  volumes of data
• Make data handling and archiving part of
  framework
• Create tools for visualization, datamining,
  pattern recognition, and data fusion

Garlock Fault
San Andreas Fault
Santa Cruz Island Fault
Santa Monica Fault
Pisgah Fault
Landers Fault
Palos Verdes Fault
San Jacinto Fault
Elsinore Fault
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SERVO Grid
Solid Earth Research Virtual Observatory Using
grid technologies and high-end computers Funded
through NASA Programs
Sensor Nets
Federated Databases
Streaming Data
Database
Loosely Coupled Filters (Coarse Graining)
Analysis and Visualization
Closely Coupled Compute Nodes
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Solid Earth Science Current and Future Directions

• 2. Develop a Solid Earth Science Problem Solving
  Environment (PSE)
• Addresses the NASA specific challenges of
  multiscale modeling
• Model and algorithm development and testing,
  visualization, and data assimilation
• Scalable to workstations or supercomputer
  depending on size of problem
• Numerical libraries existing within a compatible
  framework

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Problem Solving Environment
High-level architecture of planned system showing
grids, portals, and grid computing environments.
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Publication and Discovery Phase for Services
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Solid Earth Science Current and Future Directions

• 3. Improve the Computational Environment
• PetaFLOP computers with Terabytes of RAM
• Distributed and cluster computers for
  decomposable problems
• Development of GRID technologies

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Comments

• Earthquakes are part of interacting fault systems
  with long-range correlations.
• A substantial amount of aseismic deformation
  occurs within this system.
• Space technology is allowing us to observe these
  quiet motions for the first time giving us
  insight into the mechanical properties of the
  crust and of faults.

• New computational techniques combined with data
  analysis are required to gain insight into the
  behavior of the entire system.

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Community Involvement
Solid earth science modeling would be in the
context of the NSF Earthscope Initiative, which
calls for a NASA/space based component of the
Earth laboratory. Expand to Asia-Pacific Arc with
ACES emphasis on modeling.
The Solid Earth Science Working Group, an
independent panel of scientists, recommends
computation and modeling as part of the overall
program.
New solid earth science missions will require
computational modeling for analysis and
interpretation of the data. International
collaborations are key to success.
iSERVO Institute
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• Improvements Depend On

• Development of finite element and other modeling
  tools in a web services environment to
  incorporate multiple scales in space and time.
• New data in repositories using federated
  databases in a web services environment.
• Use of pattern recognition techniques to extract
  subtle information about the data.
• Combining components into comprehensive
  simulations constrained by data.

iSERVO Institute