Abstract
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 global navigation satellite system (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 nonlinear and anisotropic. Second, observation points are moving. Third, the measured data are 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 1000 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 min 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
Initial sea surface deformations are typically indirectly determined from seismological inversions of the earthquake source. Some of these early estimates are sometimes much lower than expected: for instance the initially estimated value for the 2011 Tohoku-Oki earthquake of Mw 7.9 was used for warnings, but the actual magnitude was Mw 9.1
These results demonstrate that our new method based on Gaussian process (GP) regression overcomes the sparsedata problem by implementing surface fitting that adequately estimated total electron content (TEC) variation with uncertainty and captured tsunami ionospheric holes (TIHs) shape
The relationship between the TIH and the initial tsunami is analyzed in more detail with the help of data provided by Tatsuhiko Saito, the first author of T
Summary
The damage caused by tsunamis can be devastating. For example, almost 20 000 people died in the tsunami following the 2011 Tohoku-Oki earthquake in Japan. 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. For each time series slant TEC data, a quadratic fitting is performed by the ordinary least-squares method for data points from 30 min before to 7 min after the time of the earthquake to be consistent with the previous study (Kamogawa et al, 2016) These fitting curves are assumed to represent the time series slant TEC data, as it would have been in the absence of the effect of TEC depression caused by acoustic waves induced by the tsunami because it takes almost 7 min for acoustic waves to reach the ionosphere. Simple but effective choices are made: the Euclidean distance is used to measure the similarity, and k is defined as the square root of the number of data points in the targeting range
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