1. D. A. Galvan1; A. Komjathy1; M. P. Hickey2; A. Mannucci1
Observing the Ionospheric Signature of Ocean Tsunamis Using GPS Total Electron Content
D. A. Galvan1; A. Komjathy1; M. P. Hickey2; A. Mannucci1
1Ionospheric and Atmospheric Remote Sensing Group, NASA Jet Propulsion Laboratory, California Institute of Technology
2Department of Physical Sciences, Embry-Riddle Aeronautical University

2. Tsunami-driven Traveling Ionospheric Disturbances (TIDs)
From Artru et al., 2005

3. Motivation: Why add ionospheric observations?
DART buoy system is expensive:
~$250,000 per buoy to build
DART system cost $12 M to maintain/operate in 2009 (28% of NOAA’s total tsunami-related budget)*
Buoys are sparsely distributed, temperamental
Data available 84% of time, outages due to harsh weather, human error*
GPS Receivers are more abundant, multi-use, low-cost
Additional means of observing tsunamis over a broader area could help to validate and improve theoretical model predictions, contributing to tsunami early warning system.
*Government Accountability Office (GAO) report, April 2010

4. Data Type: Total Electron Content (TEC) from International GNSS System (IGS) stations
-30-second TEC data from dual-frequency GPS receivers.
-Data processed through Global Ionospheric Mapping (GIM) algorithm at JPL
-For simultaneous bias identification/removal (satellite and receiver) ,

5. Regional Networks GEONET Array
Source: Scripps Orbit and Permanent Array Center (SOPAC)
GPS Data Archive, UCSD
GEONET Array
Source: Japanese GPS Earth Observation Network (GEONET) Array
Over 1200 stations

6. Streaming 1-second data availability
Currently up to 130 stations worldwide providing 1-second realtime data.
ftp://cddis.gsfc.nasa.gov/pub/gps/data/highrate

7. Methodology
Estimate arrival time. Use simple 200 m/s projection, model predictions (MOST, Song, etc.)
Process GPS TEC data JPL GIM software.
Apply bi-directional band-pass filter: 0.5 – 5 mHz (33.3 – 3 min period)
Plot filtered TEC as a function of distance/time.

8. American Samoa Tsunami 9/29/09 Observed at Hawaii
Rolland et al., 2010 (GRL)
Galvan et al., 2011 (submitted)

9. American Samoa Tsunami 9/29/09 Observed at Hawaii (map plot)
Distance from Epicenter
Lat
UT Sep 29-30, 2009
Lon

10. American Samoa Tsunami 9/29/09 Real-time 1-second data

11. COSMIC as additional resource

12. Chile Tsunami 2/27/10 Observed at Japan

13. Chile Tsunami 2/27/10 Observed at Japan
Distance from Epicenter
UT Sep 29-30, 2009

14. Theoretical Model Results
Vertical TEC
Ocean Surface
Displacement (m)
Spectral full-wave model (SFWM), Hickey et al., 2009, using input wave form from Peltier and Hines, 1976, and period/velocity from DART buoy.

15. Hickey Model Compared with Data
Filtered
VTEC
(TECU)
Universal Time (2/28/2010)

16. Summary
Tsunami-driven TID’s observed via GPS TEC after the American Samoa Tsunami of 9/29/2009 and the Chilean tsunami of 2/27/2010. (Galvan et al., submitted)
Models predict tsunami-driven TID’s.
(Occhipinti et al., 2008; Hickey et al., 2009; Mai and Kiang, 2009).
Observations: Typically ~0.1 – 0.5 TECU.
30-second archived data AND 1-second real-time data available for study, both ground-based and LEO (COSMIC).
Long-term potential for warning system.

17. Acknowledgements
NASA ROSES Grant # NNH07ZDA001N-ESI(Tsunami Imaging Using GPS Measurements)
Dr. John LaBrecque (NASA HQ)
Dr. Philip Stephens (JPL)
Dr. Vasily Titov and Dr. Yong Wei (NOAA Center for Tsunami Research)
Dr. James Foster (University of Hawaii)
Dr. Giovanni Occhipinti (IPGP, France)

18. BACKUP SLIDES

19. JPL’s GIM Ionosphere Algorithm
Data-driven vertical TEC maps based on interpolating GPS slant TEC measurements on global scales (1993 – present):
Solar-geomagnetic reference frame
Shell approximation: extended slab (450 km altitude)
Multiple shells (250, 450, & 800 km altitude)
Map slant TEC measurements to equivalent vertical using obliquity factor
Spatial interpolation: Triangular-grid or Bi-cubic splines
Temporal smoothing: stochastic Kalman filter
Vertical TEC at each vertex treated as a random walk parameter
Initialized with Klobuchar, Bent, or IRI95 model
Simultaneously solve for satellite biases (Tgd) and receiver biases