Towards the Implementation of GPS-based Tsunami Early Warning System Using Ionospheric Measurements

Friday, 19 December 2014: 12:08 PM
Yu-ming Yang, Attila Komjathy, Xing Meng, Olga P Verkhoglyadova and Anthony J Mannucci, NASA Jet Propulsion Laboratory, Pasadena, CA, United States
Natural hazards and solid Earth events, such as earthquakes, tsunamis and volcanic eruptions are actual sources that may trigger acoustic and gravity waves resulting in traveling ionospheric disturbances (TIDs) in the upper atmosphere. Trans-ionospheric radio wave measurements sense the total electron content (TEC) along the signal propagation path. In this research, we introduce a novel GPS-based detection and estimation technique for remote sensing of atmospheric wave-induced TIDs including space weather phenomena induced by major natural hazard events, using TEC time series collected from worldwide ground-based dual-frequency GNSS receiver networks.

We will demonstrate the ability of using ground-based dual-frequency GPS measures to detect and monitor tsunami wave propagations from previous great earthquake and tsunami events including: 2011 Tohoku and 2010 Chile earthquakes and tsunamis. Two major TIDs with different propagation speeds and wavelengths were identified through analysis of the GPS remote sensing observations. Dominant physical characteristics of atmospheric wave-induced TIDs are found to be associated with specific tsunami propagations and oceanic Rayleigh waves. We compared GPS-based observations, corresponding model simulations and other geophysical measurements. Our results lead to a better understanding of the tsunami-induced ionosphere responses. In addition, we investigate ionospheric signatures caused by the 1964 Great Alaska Earthquake and tsunami using the GPS-based method. Based on current distribution of Plate Boundary Observatory (PBO) GPS stations, the simulated results indicate that tsunami-induced TIDs may be detected about 60 minutes prior to tsunamis arriving at the US west coast. It is expected that this GPS-based technology becomes an integral part of future early-warning systems.