Abstract

We develop a new method to analyze the total electron content (TEC) depression in the ionosphere after a tsunami occurrence. We employ Gaussian process regression to accurately estimate the TEC disturbance every 30 s using satellite observations from the GNSS network, even over regions without measurements. We face multiple challenges. First, the impact of the acoustic wave generated by a tsunami onto TEC levels is non-linear and anisotropic. Second, observation points are moving. Third, the measured data is not uniformly distributed in the targeting range. Nevertheless, our method always computes the electron density depression volumes, along with estimated uncertainties, when applied to the 2011 Tohoku-Oki Earthquake, even with random selections of only 5 % of the 1,000 GPS Earth Observation Network System receivers considered here over Japan. Also, the statistically estimated TEC depression area mostly overlaps the range of the initial tsunami, which indicates that our method can potentially be used to estimate the initial tsunami. The method can warn of a tsunami event within 15 minutes of the earthquake, at high levels of confidence, even with a sparse receiver network. Hence, it is potentially applicable worldwide using the existing GNSS network.

Highlights

  • We develop a new method to analyze the total electron content (TEC) depression in the ionosphere after a tsunami occurrence

  • It can be seen that the 150 measurement points are moving and are not uniformly distributed in the targeting range, which is from 33.297◦N to 43.297◦N in latitude and from 137.373◦E to 147.373◦E in longitude. It can be confirmed from panels (c) and (d) that the Tsunami Ionospheric Holes (TIHs) is formed, we argue that a single data point alone such as the minimum TEC value is not enough to evaluate the scale of TIH

  • Unlike the case of full data displayed in panel (a), it can be clearly seen from panel (b) that the number of data points in the sparse data case is not sufficient to entirely analyze TIH, where 95% of the GNSS receivers are randomly removed from 200 the observed data

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Summary

Introduction

The damage caused by tsunamis can be devastating. For example, almost 20,000 people died in the tsunami following the 2011 Tohoku tsunami in Japan. The most prominent case of the TEC changes in the ionosphere observed by GEONET is the tsunami following the 2011 Earthquake, off of the Pacific coast of Tohoku. In regions where GNSS observation networks are less dense, the number of available data is even smaller, making it very difficult to detect the TIH confidently. To overcome these problems, we implement below a statistical method for the analysis of TEC using satellite data, which allows us to estimate TEC values even over areas with no measurements and to evaluate the whole TIH even without a dense measurement network such as GEONET in Japan.

Data and Method
Results
Outlier detection
Surface fitting with sparse data
TIH expansion
TIH expansion distance in each direction
TIH overlapping with initial tsunami
TIH volume computation
Conclusions
395 References
Full Text
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