Pure and Applied Geophysics

, Volume 173, Issue 12, pp 3863–3880 | Cite as

Consistent Estimates of Tsunami Energy Show Promise for Improved Early Warning

  • V. Titov
  • Y. Tony Song
  • L. Tang
  • E. N. Bernard
  • Y. Bar-Sever
  • Y. Wei
Article

Abstract

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.

Keywords

Tsunami energy GPS network DART system early warning 

Supplementary material

24_2016_1312_MOESM1_ESM.docx (1.5 mb)
Supplementary material 1 (DOCX 1533 kb)

References

  1. 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
  2. Ando, M., Ishida, M., Hayashi, Y., & Mizuki, C. (2011). Interviews with survivors of Tohoku earthquake provide insights into fatality rate. EOS Transitions AGU, 92(48), 411–412.CrossRefGoogle Scholar
  3. Bernard, E. N., & Titov, V. V. (2015). Evolution of tsunami warning systems and products. PPhilosophical Transactions of the Royal Society. doi:10.1098/rsta.2014.0371.Google Scholar
  4. Bernard, E. N., Wei, Y., Tang, L., & Titov, V. V. (2014). Impact of near-field, deep-ocean tsunami observations on forecasting the 7 December 2012 Japanese Tsunami. Pure and Applied Geophysics, 171 (12), 3483–3491. doi:10.1007/s00024-013-0720-8.CrossRefGoogle Scholar
  5. Blewitt, G., Kreemer, C., Hammond, W. C., Plag, H.-P., Stein, S., & Okal, E. (2006). Rapid determination of earthquake magnitude using GPS for tsunami warning systems. Geophysical Research Letters 33, L11309. doi:10.1029/2006GL026145.CrossRefGoogle Scholar
  6. Degueldre, H., Metzger, J. J., Geisel, T., & Fleischmann, R. (2016). Random focusing of tsunami waves. Nature Physics, 12, 259–262. doi:10.1038/nphys3557.CrossRefGoogle Scholar
  7. 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
  8. 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
  9. Gusman, A. R., Tanioka, Y., Sakai, S., & Tsushima, H. (2012). Source model of the great 2011 Tohoku earthquake estimated from tsunami waveforms and crustal deformation data. Earth and Planetary Science Letters, 341, 234–242.CrossRefGoogle Scholar
  10. Hammack, J. L., & Segur, H. (1974). The Korteweg-de Vries equation and water waves. Part 2. Comparison with experiments. Journal of Fluid Mechanics, 65(Part 2), 289–314.CrossRefGoogle Scholar
  11. 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
  12. Imamura, A. (1942). History of Japanese tsunamis. Kayo-No-Kagaku (Oceanography), 2, 74–80. (in Japanese).Google Scholar
  13. Ito, Y., et al. (2011). Frontal wedge deformation near the source region of the 2011 TohokuOki earthquake. Geophysical Research Letters, 38, L00G05.CrossRefGoogle Scholar
  14. 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.
  15. Kanoglu, U., Titov, V., Bernard, E., & Synolakis, C. (2015 ). Tsunami; bridge the science, engineering and social science. Philosophical Transactions of the Royal Society A, 373(2053), 20140369.CrossRefGoogle Scholar
  16. Kanoglu, U., & Synolakis, C. E. (2006). Initial value problem solution of nonlinear shallow water wave equations. Physical Review Letters, 97(14), 148501. doi:10.1103/PhysRevLett.97.148501.CrossRefGoogle Scholar
  17. 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
  18. Mei, C. C., Tiassnie, M., & Yue, D. (2005). Theory and applications of ocean surface waves, part 1: Linear aspects. Singapore: World Scientific.Google Scholar
  19. Morgan, R. (2011). Top 100 stories of 2010, #84: Yardstick for killer waves, Discover. http://discovermagazine.com/2011/jan-feb/84/.
  20. Murty, T. S., & Loomis, H. G. (1980). A new objective tsunami magnitudes scale. Marine Geodesy, 4, 267–282.CrossRefGoogle Scholar
  21. 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/.
  22. 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
  23. Okal, E. A. (2015). The quest for wisdom: Lessons from 17 tsunamis, 2004–2014. Philosophical Transactions of the Royal Society A, 373, 20140370. doi:10.1098/rsta.2014.0370.CrossRefGoogle Scholar
  24. Okal, E. A., & Synolakis, C. E. (2016). Sequencing of tsunami waves: Why the first wave is not always the largest. Geophysical Journal International, 204(2), 719–735.CrossRefGoogle Scholar
  25. 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
  26. Percival, D. B., Denbo, D. W., Eble, M. C., Gica, E., Mofjeld, H. O., Spillane, M. C., et al. (2011). Extraction of tsunami source coefficients via inversion of DART® buoy data. Natural Hazards, 58(1), 567–590. doi:10.1007/s11069-010-9688-1.CrossRefGoogle Scholar
  27. Satake, K., Nishimura, Y., Putra, P. S., Gusman, A. R., Sunendar, H., Fujii, Y., & Yulianto, E. (2013). Tsunami source of the 2010 Mentawai, Indonesia earthquake inferred from tsunami field survey and waveform modeling. Pure and Applied Geophysics, 170(9–10), 1567–1582.CrossRefGoogle Scholar
  28. Sieberg, A. (1927). Geologische, physikalische and angewandte Erdbebenkunde. Jena: Verlag von Gustav Fischer.Google Scholar
  29. Song, Y. T., Ji, C., Fu, L.-L., Zlotnicki, V., Shum, C. K., Yi, Y., & Hjorleifsdottir, V. (2005). The 26 December 2004 Tsunami source estimated from satellite radar altimetry and seismic waves. Geophysical Research Letters,. doi:10.1029/2005GL023683.Google Scholar
  30. Song, Y. T. (2007). Detecting tsunami genesis and scales directly from coastal GPS stations. Geophysical Research Letters, 34, L19602. doi:10.1029/2007GL031681.CrossRefGoogle Scholar
  31. Song, Y. T., Fu, L.-L., Zlotnicki, V., Ji, C., Hjorleifsdottir, V., Shum, C. K., & Yi, Y. (2008). The role of horizontal impulses of the faulting continental slope in generating the 26 December 2004 Tsunami. Ocean Modelling,. doi:10.1016/j.ocemod.2007.10.007.Google Scholar
  32. Song, Y. T., & Han, S. C. (2011). Satellite observations defying the long-held tsunami genesis theory. In D. L. Tang (Ed.), Remote sensing of the changing oceans. Berlin: Springer. doi:10.1007/978-3-642-16541-2.Google Scholar
  33. Song, Y. T., Fukumori, I., Shum, C. K., & Yi, Y. (2012). Merging tsunamis of the 2011 Tohoku-Oki earthquake detected over the open ocean. Geophysical Research Letters, 39, L05606. doi:10.1029/2011GL050767.Google Scholar
  34. Stein, S., & Okal, E. A. (2005). Speed and size of the Sumatra earthquake. Nature, 434(7033), 581–582.CrossRefGoogle Scholar
  35. Synolakis, C., Bernard, E., Titov, V., Kanoglu, U., & Gonzalez, F. (2008). Validation and verification of tsunami numerical models. Pure and Applied Geophysics, 165(11–12), 2197–2228. doi:10.1007/s00024-004-0427-y.CrossRefGoogle Scholar
  36. Tang, L., Titov, V. V., & Chamberlin, C. D. (2009). Development, testing, and applications of site-specific tsunami inundation models for real-time forecasting. Journal of Geophysical Research, 114, C12025. doi:10.1029/2009JC005476.CrossRefGoogle Scholar
  37. Tang, L., Titov, V. V., Wei, Y., Mofjeld, H. O., Spillane, M., Arcas, D., et al. (2008). Tsunami forecast analysis for the May 2006 Tonga tsunami. Journal of Geophysical Research, 113, C12015. doi:10.1029/2008JC004922.CrossRefGoogle Scholar
  38. Tang, L., Titov, V. V., Bernard, E. N., Wei, Y., Chamberlin, C. D., Newman, J. C., et al. (2012). Direct energy estimation of the 2011 Japan tsunami using deep-ocean pressure measurements. Journal of Geophysical Research, 117, C08008. doi:10.1029/2011JC007635.Google Scholar
  39. 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
  40. Tanioka, Y., & Satake, K. (1996). Tsunami generation by horizontal displacement of ocean bottom. Geophysical Research Letters, 23(8), 861–864.CrossRefGoogle Scholar
  41. Titov, V. V., & Synolakis, C. E. (1995). Modeling of Breaking and Nonbreaking Long Wave Evolution and Runup using VTCS-2. Journal of Waterways, Ports, Coastal and Ocean Engineering, 121(6), 308–316.CrossRefGoogle Scholar
  42. Titov, V. V., & Synolakis, C. E. (1998). Numerical modeling of tidal wave runup. Journal of Waterway, Port, Coastal and Ocean Engineering, 124(4), 157–171.CrossRefGoogle Scholar
  43. 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
  44. 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
  45. Titov, V. V., González, F. I., Bernard, E. N., Eble, M. C., Mofjeld, H. O., Newman, J. C., & Venturato, A. J. (2005). Real-time tsunami forecasting: Challenges and solutions. Natural Hazards, 35(1), 41–58.CrossRefGoogle Scholar
  46. Titov, V. V. (2009). Tsunami forecasting. In E. N. Bernard (Ed.), The Sea, Tsunamis Ch. 12 (15th ed.). Cambridge: Harvard Univ. Press.Google Scholar
  47. 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
  48. Wei, Y., Bernard, E. N., Tang, L., Weiss, R., Titov, V. V., Moore, C., et al. (2008). Real-time experimental forecast of the Peruvian tsunami of August 2007 for US coastlines. Geophysical Research Letters, 35, L04609. doi:10.1029/2007GL032250.Google Scholar
  49. 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.
  50. Wei, Y., Chamberlin, C., Titov, V., Tang, L., & Bernard, E. N. (2013). Modeling of the 2011 Japan tsunami—lessons for near-field forecast. Pure and Applied Geophysics, 170(6–8), 1309–1331. doi:10.1007/s00024-012-0519-z.CrossRefGoogle Scholar
  51. 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
  52. Xu, Z., & Song, Y. T. (2013). Combining the all-source Green’s functions and the GPS-derived source for fast tsunami prediction—illustrated by the March 2011 Japan tsunami. Journal of Atmospheric and Oceanic Technology. doi:10.1175/JTECH-D-12-00201.1.Google Scholar

Copyright information

© Springer Basel (outside the USA) 2016

Authors and Affiliations

  • V. Titov
    • 1
  • Y. Tony Song
    • 2
  • L. Tang
    • 1
    • 3
  • E. N. Bernard
    • 1
  • Y. Bar-Sever
    • 2
  • Y. Wei
    • 1
    • 3
  1. 1.NOAA Center for Tsunami Research, Pacific Marine Environmental LaboratoryNational Oceanic and Atmospheric AdministrationSeattleUSA
  2. 2.Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaUSA
  3. 3.Joint Institute for the Study of the Atmosphere and OceanUniversity of WashingtonSeattleUSA

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