11:45 AM - 12:00 PM
[SCG63-05] Development of Waveform Filters for Real-time Tsunami Forecasting using Ocean Bottom Pressure Data
Keywords:Tsunami, Realtime forecasting, Waveform filter
Offshore tsunami observation is really effective in terms of real-time tsunami forecasting because it enables us to observe tsunamis (sea surface disturbance) caused by earthquakes and other phenomena before the tsunami reaches land side. The Deep-ocean Assessment and Reporting of Tsunamis (DART) is usually installed in deep water near the trench axes, where huge earthquakes have periodically occurred. On the other hand, in order to observe tsunami around Japan, the Seafloor observation network for earthquakes and tsunamis along the Japan Trench (S-net), the Dense Oceanfloor Network System for Earthquakes and Tsunamis (DONET), and the Nankai Trough Seafloor Observation Network for Earthquakes and Tsunamis (N-net) have been installed not only in deep sea but also in shallow water near the land side. These observation networks record sea level changes as pressure changes using pressure gauges installed on the seafloor to observe tsunami. In many research purpose and monitoring operations, hydrostatic equilibrium could be implicitly assumed, therefore, the ocean bottom pressure changes ΔP is assumed to be multiple of the sea water density ρ, gravitational acceleration constant g, and wave heights at the sea surface η. On the other hand, theoretically, it is well known that the ocean bottom pressure changes attenuate by 1/cosh(kh) at the location of a sea depth of h with respect to the spatial wavenumber k of the sea surface spatial distributions, and its effect on the tsunami waveform has also been confirmed.
In order to detect tsunamis using the ocean bottom pressure data in real-time, a trigger that a tsunami is occurring is required. For seismic tsunamis, the time of earthquake occurrence can be used as a tsunami detection trigger, but for non-seismic tsunamis, we should consider a trigger to detect the tsunami using only ocean bottom pressure changes. As the simplest method, the ratio of the short-term to the long-term average of the waveform amplitude is commonly used. In such methods, tsunami occurrence is detected when the ratio exceeds a threshold level given in advance. There are other detection methods, but most of them are based on amplitude alone and do not use wavelength of tsunami. Therefore, using data from a wide-area observation network causes different sensitivity due to the difference in water depth at the gauge location. In addition, it is necessary to change the threshold value because wind waves, which generally have shorter wavelengths than tsunamis, cause false detection at stations with shallower water depths, but quantitative discussions have not been conducted.
In this study, we propose a method for setting the threshold independent of water depth by applying a filter to the waveform at a hypothetical uniform water depth, based on the wave number and sea depth dependent attenuation rate. We also report the results of our study on appropriate filters for tsunami detection, such as a method to deal with steps of ocean bottom pressure of an in-line ocean bottom pressure gauge and waveform deformation due to tidal change removing using a Butterworth filter, etc.
In order to detect tsunamis using the ocean bottom pressure data in real-time, a trigger that a tsunami is occurring is required. For seismic tsunamis, the time of earthquake occurrence can be used as a tsunami detection trigger, but for non-seismic tsunamis, we should consider a trigger to detect the tsunami using only ocean bottom pressure changes. As the simplest method, the ratio of the short-term to the long-term average of the waveform amplitude is commonly used. In such methods, tsunami occurrence is detected when the ratio exceeds a threshold level given in advance. There are other detection methods, but most of them are based on amplitude alone and do not use wavelength of tsunami. Therefore, using data from a wide-area observation network causes different sensitivity due to the difference in water depth at the gauge location. In addition, it is necessary to change the threshold value because wind waves, which generally have shorter wavelengths than tsunamis, cause false detection at stations with shallower water depths, but quantitative discussions have not been conducted.
In this study, we propose a method for setting the threshold independent of water depth by applying a filter to the waveform at a hypothetical uniform water depth, based on the wave number and sea depth dependent attenuation rate. We also report the results of our study on appropriate filters for tsunami detection, such as a method to deal with steps of ocean bottom pressure of an in-line ocean bottom pressure gauge and waveform deformation due to tidal change removing using a Butterworth filter, etc.