Description
Tsunamis are among the most devastating natural hazards, leading to significant human casualties. They are typically triggered by submarine earthquakes, volcanic eruptions, or landslide, and predicting their impact remains extremely challenging.
Although various techniques are currently employed to monitor tsunami propagatio in both the near-field (within 500 km of the source) and ther far field (beyond 500 km), such as seafloor pressure sensors, DART buoys, and tide gauges, tsunami monitoring continues to be highly challenging.
It is well etablished that tsunami propagation generates internal gravity waves that can be observed in the ionosphere within 20-60 minutes after their formation at the ocean surface [1,2]. By analyzing total electron content (TEC) measurements obtained from GNSS receivers, co-tsunamic ionospheric disturbances (CTIDs) can be detected, and tsunami characteristics can be inferred from properties of these disturbances. However, numerous phenomena originating from both terrestrial and space sources also produce gravity waves, which may be interpreted as tsunami-related signals. In particular, the solar terminator -corresponding to the day-nigth transition - is a key factor to consider in CTID detection due to its regular and predicable occurence.
On July 29 2025, a Mw 8.8 earthquake struck near the southern coast of Kamchatka, generating a tsunami that propagated across the Pacific Ocean. This event represents the strongest earthquake since the March 2011 Tohoku-Oki earthquake, offering a valuable opportunity to identify, within TEC time series, the essential parameters needed to differenciate CTIDs from solar temrinator effects, as well as to investigate and characterize the associated tsunami signal. In this study, we present a comprehensive analysis of the spatio-temporal characteristics of CTIDs in the Hawaii region.
[1] C.O.Hines, Can.J.Phys. 38, 1441(1960).
[2] J.Hong,H.Kil, W.K.Lee, Y.S.Kwak, B.K.Choi, and L.J.Paxton, Geophys.Res.Lett.49, e2022GL099163(2022).
| Speaker information | PhD 2nd year |
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