2011 Tohoku Earthquake: Tsunami GPS Buoy Processing

Tsunami Signal Detected at Hiratsuka-oki Buoy with RTNet PPP

March 15, 2011

Tsunami Buoy

A one-meter tsunami first arrives at the Hiratsuka buoy at about 6:35 UTC. It is interesting to note the change in buoy motion at about 5:50 UTC (most visible in the 11-sec running average) which appears to coincide with the arrival of seismic waves. The shown PPP solutions was computed with the real-time global orbit and clock product from the VERIPOS/APEX service.

Acknowledgement: The tsunami buoy data is provided from Uviversity of Tokyo (Meguro Lab.)


Proposal of New GPS Tsunami Buoy Network for Urgent Warning

Proposal of GNSS buoy network

There are limitations of location in current GPS tsunami buoy system in Japan:

  • Distance of buoy from ocean coast is about 20km because of receiver-based RTK (no data is saved/transferred to the land)
  • Then, relatively short time warning (only a few minutes) is possible

To overcome the problems above, we propose new GPS tsunami buoy network in the map above (blue circles and red circles are both GPS buoy stations, but blue stations locate closer to ocean coast than red ones).

Note that we need thin out the stations to save budget based on risk assessment for tsunami and earthquakes based on historical records.

Each GPS buoy station has data transmission system of observation data, and send observation to processing center through satellite communication. The buoy GPS data is processed with PPP kinematic positioning based on real-time satellite orbit and clock products estimated from global GPS network. The recommended constrain for coordinate is set as almost open (100 m/s).

Tsunami with lower height is also detectable if we focus on correlation of height solutions with time delay for red and blue stations.

The GPS buoy system is multi purpose focusing on environmental monitoring. We can estimate tropospheric delay at the buoy stations, and these information could be used as input for numerical weather model to improve water vapor field in the model and to improve severe precipitation forecast. Also, the information could be used for calibration for other water vapor observation from satellite.