Tsunami Data Assimilation of Cabled Ocean Bottom Pressure Records for the 2015 Torishima Volcanic Tsunami Earthquake. Issue 10 (23rd October 2019)

• Record Type: Journal Article
• Authors: Wang, Y.; Satake, K.; Sandanbata, O.; Maeda, T.; Su, H.
• Is Part Of: Journal of geophysical research. Volume 124:Issue 10(2019)
• Page Start: 10413
• Page End: 10422
• Publication Date: 2019-10-23
• Subjects: data assimilation -- Torishima earthquake -- tsunami early warning -- ocean bottom pressure gauge; Geomagnetism -- Periodicals; Geochemistry -- Periodicals; Geophysics -- Periodicals; Earth sciences -- Periodicals; 551.1
• DOI: 10.1029/2019JB018056
• Languages: English
• ISSNs: 2169-9313

Abstract

Abstract: Abnormal volcanic earthquakes occurring near the volcanic island of Torishima, south of Japan, sometimes generate relatively larger tsunamis compared to the seismic magnitudes. They have a non‐double‐couple focal mechanism known as compensated linear vector dipole. The unusual earthquake source mechanism poses difficulties in traditional tsunami forecasting method based on seismic parameters. Tsunami data assimilation, a method of tsunami forecast using offshore tsunami observation data and numerical model, avoids the complexities and uncertainties in the tsunami source estimation and makes a tsunami early warning at coastal points of interest. Along Nankai trough, many offshore bottom pressure gauges are installed, and the data are transmitted in real time through submarine cables. Previous synthetic experiments have demonstrated the capability of the data assimilation approach for tsunami forecasting. In this paper, we report the successful application of the tsunami data assimilation to the cabled ocean bottom pressure gauge data for the first time. We assimilated the tsunami data recorded on ocean bottom pressure gauges to retroactively forecast the tsunamis of the 2015 Torishima earthquake. Comparison of the forecasted and observed waveforms at two coastal tide gauges (Kushimoto and Tosashimizu) confirmed that our method could forecast the tsunami amplitude and arrival time accurately, merely based on offshore tsunami observations. We also investigated the relationship between the number of observational stations used for assimilation and the forecasting accuracy and determined which stations were more important in data assimilation. Key Points: Tsunami data assimilation was applied to offshore bottom pressure records of the 2015 Torishima volcanic tsunami earthquake Forecasted tsunami arrival times and amplitudes, without assuming the source, were similar to the tide gauge records Relation between forecast accuracy and number of stations used for assimilation was investigated by calculating general error function