Shinji Hirooka

Ionospheric anomaly as an earthquake precursor: Case and statistical studies during 1998–2012 around Japan

Many anomalous electromagnetic phenomena possibly associated with large earthquakes have been reported. TEC (Total Electron Contents) anomaly is one of the most promising phenomena preceding large earthquakes. We investigated statistically TEC anomalies before large earthquakes around Japan region during 1998-2012. In this study, superposed epoch analysis (SEA) and Molchans error diagram (MED) analysis have been taken to investigate correlation and predictability in the statistical manner. The results of SEA show that positive anomaly 1-5 days before the large earthquake (M>=6.0 and depth <;= 40 km) is significant. The results of MED analysis indicate the some gain against the random estimation (Poisson model). That is, the prediction using TEC anomaly around Japan is not random and has an information. Furthermore, in order to understand the mechanism, monitoring of 3D distributions of ionospheric electron density is considered to be effective. In this study, to investigate the three-dimensional structure of ionospheric electron density prior to large earthquake, the neural network based tomographic approach is adapted to GEONET and ionosonde data for the 2011 Off the Pacific Coast of Tohoku Earthquake (Mw9.0) and other earthquake which investigated in above statistical analysis. As for the M9 Tohoku earthquake, the reconstructed distribution of electron density decreases just below the F-region and was enhanced over F-region in comparison with 15 days backward median distribution. Moreover the enhanced area seems to be developed to upper ionosphere from sub-ionosphere with time. Similar precursor tendency is found for the earthquake with longer duration of GIM-TEC anomalies. These tomographic results suggest the existence of additive horizontal electric field of eastward, which is possibly related to the seismic activity. The details will be shown in the presentation.

Neural network based tomographic approach to detecting the ionospheric anomalies prior to the 2007 Southern Sumatra earthquake

In this paper, neural network based ionospheric tomography was performed to investigate the detailed structure that may be associated with earthquakes. The 2007 Southern Sumatra earthquake (M8.5) is selected because significant decreases in the Total Electron Content (TEC) have been confirmed by GPS data analysis. With respect to the analyzed earthquake, we detected significant decreases at heights of 250–400 km, especially at 300 km. The global tendency is that the decreased region expands to the east with increasing altitude and concentrated in the Southern hemisphere over the epicenter. Furthermore, obtained results are consistent with other satellite observation.

Development and validation of neural network based ionospheric tomography

In order to investigate the dynamics of ionospheric phenomena, perform the 3-D ionospheric tomography is effective. However, it is the ill-posed inverse problem and reconstruction is difficult because of the small number of data. The Residual Minimization Training Neural Network (RMTNN) tomographic approach proposed by Ma et al. [3] has an advantage in reconstruction with sparse data. They have demonstrated few results in quiet conditions of ionosphere in Japan. Therefore, we validate the performance of reconstruction in the case of disturbed period and quite sparse data by the simulation and/or real data in this paper.