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. 2017 Apr 21:7:46607.
doi: 10.1038/srep46607.

Real-Time Detection of Tsunami Ionospheric Disturbances with a Stand-Alone GNSS Receiver: A Preliminary Feasibility Demonstration

Giorgio Savastano  1 , Attila Komjathy  2 , Olga Verkhoglyadova  2 , Augusto Mazzoni  1 , Mattia Crespi  1 , Yong Wei  3   4 , Anthony J Mannucci  2
Affiliations

Real-Time Detection of Tsunami Ionospheric Disturbances with a Stand-Alone GNSS Receiver: A Preliminary Feasibility Demonstration

Giorgio Savastano et al. Sci Rep. .

Abstract

It is well known that tsunamis can produce gravity waves that propagate up to the ionosphere generating disturbed electron densities in the E and F regions. These ionospheric disturbances can be studied in detail using ionospheric total electron content (TEC) measurements collected by continuously operating ground-based receivers from the Global Navigation Satellite Systems (GNSS). Here, we present results using a new approach, named VARION (Variometric Approach for Real-Time Ionosphere Observation), and estimate slant TEC (sTEC) variations in a real-time scenario. Using the VARION algorithm we compute TEC variations at 56 GPS receivers in Hawaii as induced by the 2012 Haida Gwaii tsunami event. We observe TEC perturbations with amplitudes of up to 0.25 TEC units and traveling ionospheric perturbations (TIDs) moving away from the earthquake epicenter at an approximate speed of 316 m/s. We perform a wavelet analysis to analyze localized variations of power in the TEC time series and we find perturbation periods consistent with a tsunami typical deep ocean period. Finally, we present comparisons with the real-time tsunami MOST (Method of Splitting Tsunami) model produced by the NOAA Center for Tsunami Research and we observe variations in TEC that correlate in time and space with the tsunami waves.

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Conflict of interest statement

The authors declare no competing financial interests.

Figures

Figure 1
Figure 1. Map indicating the epicenter of the 10/27/2012 Haida Gwaii earthquake (left panel) and zoomed-in image of the Hawai’i Big Island, where all the 56 used GPS stations are located.
The map has been generated using the matplotlib Basemap toolkit.
Figure 2
Figure 2. Comparison between TEC time series obtained from the VARION and JPL techniques.
The TEC variations are computed for 7 satellites (PRNs 4, 7, 8, 10, 13, 20, 23) in view from the AHUP station on the Hawaiian Islands (latitude: 19.379 degrees, longitude: −155.266 degrees, height: 1104.881 meters). The black vertical line represents the time when the tsunami reached the Hawaiian Islands. TIDs were clearly detected, with good agreement between the two approaches.
Figure 3
Figure 3
(a,b,e,f) Four of 260 time series used for the wavelet analysis, station AHUP, satellite PRN 4, 7, 8, 10. (c,d,g,h) The wavelet power spectrum used the Paul wavelet. The vertical axis displays the Fourier period (in min), the horizontal axis is time (s). The black vertical line represents the time when the tsunami reached the Hawaiian islands. The color panels represent the intensity of the power spectrum; the black contour encloses regions of greater than 95% confidence for a red-noise process with a lag-1 coefficient of 0.72; the external black line indicates the “one of influence”, the limit outside of which edge effects may become significant. We clearly see the increase of the power spectrum for periods between 10 and 30 minutes during the TIDs.
Figure 4
Figure 4
(i,l,o) Three of 260 time series used for the wavelet analysis, station AHUP, satellite PRN 13, 20, 23. (m,n,p) The wavelet power spectrum used the Paul wavelet. The vertical axis displays the Fourier period (in min), the horizontal axis is time (s). The black vertical line represents the time when the tsunami reached the Hawaiian islands. For satellites PRN 13 and 23 we do not see significant increase of the power spectrum for periods between 10 and 30 minutes during the TIDs.
Figure 5
Figure 5. Space–time sTEC variations for two hours (08:00 to 10:00 UT – 28 October 2012 – cut–off angle set to 18°) at the SIPs (same positions of the corresponding IPPs on the map) for the 7 satellites seen from the 56 Hawaiian Hawaii Islands GPS permanent stations, after the Haida Gwaii earthquake.
The TIDs are clearly visible in the interval of significant sTEC variations (from positive to negative values and vice-versa). It is also shown that PRN 10 detected TIDs prior to the tsunami arrival at Hawaiian Islands (08:30:08 UT). The map has been generated using the matplotlib Basemap toolkit.
Figure 6
Figure 6. sTEC variations for two hours (08:00 to 10:00 UT – 28 October 2012) at the IPPs vs. distance from the Haida Gwaii earthquake epicenter, for the 7 satellites observed from the 56 Hawaii Hawaiian Islands GPS permanent stations.
The TIDs are clearly visible in the interval of significant sTEC variations (from positive to negative values and vice-versa). The vertical and horizontal black lines represent the time (when the tsunami arrived at the Hawaiian Islands) and the distance (between the epicenter and the Big Island), respectively; it is evident that PRN 10 detected TIDs before the tsunami arrived at Hawaiian Hawaii Islands (08:30:08 UT). The slope of the straight line fitted, considering a linear least-squares regression for corresponding sTEC minima for different satellites, represent the TIDs mean propagation velocity.
Figure 7
Figure 7. Space-time sTEC variations at 6 epochs within the two hours interval (08:00 to 10:00 UT – 28 October 2012) at the SIPs for the 5 satellites showing TIDs, overplotted the tsunami MOST model.
TIDs are consistent in time and space with the tsunami waves. The maps have been generated using the matplotlib Basemap toolkit.
Figure 8
Figure 8. Schematic representation of the TID detection at t1 and t2 = t1 + Δt by two different satellites S1 and S2.
R represents the receiver, hmodel and hreal represent the modeled ionospheric layer and the real ionospheric layer. In this case the two layers are located at 300 and 350 km, respectively.
See this image and copyright information in PMC

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