Consistent Estimates of Tsunami Energy Show Promise for Improved Early Warning
- 417 Downloads
Early tsunami warning critically hinges on rapid determination of the tsunami hazard potential in real-time, before waves inundate critical coastlines. Tsunami energy can quickly characterize the destructive potential of generated waves. Traditional seismic analysis is inadequate to accurately predict a tsunami’s energy. Recently, two independent approaches have been proposed to determine tsunami source energy: one inverted from the Deep-ocean Assessment and Reporting of Tsunamis (DART) data during the tsunami propagation, and the other derived from the land-based coastal global positioning system (GPS) during tsunami generation. Here, we focus on assessing these two approaches with data from the March 11, 2011 Japanese tsunami. While the GPS approach takes into consideration the dynamic earthquake process, the DART inversion approach provides the actual tsunami energy estimation of the propagating tsunami waves; both approaches lead to consistent energy scales for previously studied tsunamis. Encouraged by these promising results, we examined a real-time approach to determine tsunami source energy by combining these two methods: first, determine the tsunami source from the globally expanding GPS network immediately after an earthquake for near-field early warnings; and then to refine the tsunami energy estimate from nearby DART measurements for improving forecast accuracy and early cancelations. The combination of these two real-time networks may offer an appealing opportunity for: early determination of the tsunami threat for the purpose of saving more lives, and early cancelation of tsunami warnings to avoid unnecessary false alarms.
KeywordsTsunami energy GPS network DART system early warning
This research is partially funded by the NOAA Center for Tsunami Research, PMEL contribution 4405, and by the Joint Institute for the Study of the Atmosphere and Ocean (JISAO) under NOAA Cooperative Agreement NA10OAR4320148 (2010–2015) and NA15OAR4320063 (2015–2020), Contribution No. 2497. Part of the research carried out by Y. T. Song and Y. Bar-Sever here was conducted at the Jet Propulsion Laboratory, California Institute of Technology, under contract “GPS-Aided and DART-Ensured Real-time (GADER) Tsunami Early Detection System” with the National Aeronautics and Space Administration (NASA).
- Ambraseys, N. N. (1962). Data for the investigation of seismic sea waves in the Eastern Mediterranean. Bulletin of the Seismological Society of America 52, 895–913.Google Scholar
- Gica, E., Spillane, M. C., Titov, V. V., Chamberlin, C. D., & Newman, J. C. (2008). Development of the forecast propagation database for NOAA’s Short-term Inundation Forecast for Tsunamis (SIFT). NOAA technical memorandum OAR PMEL-139, NTIS: PB2008-109391. Seattle:NOAA/Pacific Marine Environmental Laboratory.Google Scholar
- Gusiakov, V. K. (1978). Static displacement on the surface of an elastic space, in Ill-Posed Problems of Mathematical Physics and Interpretation of Geophysical Data (in Russian) (pp. 23–51). Novosibirsk: Comput. Cent. of Sov. Acad. of Sci.Google Scholar
- Iida, K. (1956). Earthquakes accompanied by tsunamis occurring under the sea off the islands of Japan. Journal of Earth Sciences, Nagoya University, 4, 1–43.Google Scholar
- Imamura, A. (1942). History of Japanese tsunamis. Kayo-No-Kagaku (Oceanography), 2, 74–80. (in Japanese).Google Scholar
- Jouhana, D., & Paddock R. C. (2006). Indonesia quake kills 3500, Chicago Tribune. http://articles.chicagotribune.com/2006-05-28/news/0605280253_1_bantul-quake-caused-widespread-panic-rush-tents.
- Liu, P. L. F. (2009). Tsunami modeling: Propagation. In E. Bernard, et al. (Eds.), The Sea, Tsunamis Ch. 3 (15th ed., pp. 295–320). Cambridge: Harvard University Press.Google Scholar
- Mei, C. C., Tiassnie, M., & Yue, D. (2005). Theory and applications of ocean surface waves, part 1: Linear aspects. Singapore: World Scientific.Google Scholar
- Morgan, R. (2011). Top 100 stories of 2010, #84: Yardstick for killer waves, Discover. http://discovermagazine.com/2011/jan-feb/84/.
- Naranjo, L. (2013). Sizing a tsunami, sensing out planet. NASA Sciene Research Features 2013, pp. 30–33. https://earthdata.nasa.gov/featured-stories/featured-research/sizing-tsunami/.
- NASA release (2010). http://www.nasa.gov/topics/earth/features/tsunami_prediction.html.
- Okada, Y. (1985). Surface deformation due to shear and tensile faults in a half space. Bulletin of the Seismological Society of America, 75, 1135–1154.Google Scholar
- Papadopoulos, G. A., & Imamura, F. (2001). A proposal for a new tsunami intensity scale Internat. Tsunami sympocium 2001 Proc., Seattle, Washington, Aug. 7–10, 2001, pp. 569–577.Google Scholar
- Sieberg, A. (1927). Geologische, physikalische and angewandte Erdbebenkunde. Jena: Verlag von Gustav Fischer.Google Scholar
- Tang, L., Titov, V. V., Moore, C., & Wei, Y. (2015). Real-time assessment of the 16 September 2015 Chile Tsunami and implications for near-field forecast. Pure and Applied Geophysics. (in review).Google Scholar
- Titov, V. V., & Gonzalez, F. I. (1997). Implementation and testing of the Method of Splitting Tsunami (MOST) model. NOAA Tech. Memo. ERL PMEL-112. Seattle: Pacific Marine Environmental Laboratory.Google Scholar
- Titov, V. V., Mofjeld, H. O., Gonzalez, F. I., & Newman, J. C. (1999). Offshore forecasting of Alaska-Aleutian subduction zone tsunamis in Hawaii, Tech. Memo. ERL PMEL-114 (p. 22). Seattle: Gov. Print. Off..Google Scholar
- Titov, V. V. (2009). Tsunami forecasting. In E. N. Bernard (Ed.), The Sea, Tsunamis Ch. 12 (15th ed.). Cambridge: Harvard Univ. Press.Google Scholar
- Titov, V. V., Moore, C. W., Greenslade, D. J. M., Pattiaratchi, C., Badal, R., Synolakis, C. E., & Kanoglu, U. (2011). A new tool for inundation modeling: Community Modeling Interface for Tsunamis (ComMIT). Pure and Applied Geophysics, 168, 2121–2131. doi: 10.1007/s00024-011-0292-4.CrossRefGoogle Scholar
- Wei, Y., Chamberlin, C., Titov, V. V., Tang, L., & Bernard, E. N. (2012). Modeling of 2011 Japan Tsunami: Lessons for near-field forecast. Pure and Applied Geophysics. doi: 10.1007/s00024012z.
- Wei, Y., Newman, A. V., Hayes, G. P., Titov, V. V., & Tang, L. (2014). Tsunami forecast by joint inversion of real-time tsunami waveforms and seismic or GPS data: Application to the Tohoku 2011 tsunami. PPure and Applied Geophysics, 171(12), 3281–3305. doi: 10.1007/s00024-014-0777-z.CrossRefGoogle Scholar