Evaluation of the Express Method Effectiveness in Short-Term Forecasting on the Examples of the Peruvian (2007) and the Chilean (2010, 2014 and 2015) Tsunamis

Yu. P. Korolev

Institute of Marine Geology and Geophysics, Far Eastern Branch of Russian Academy of Sciences, Yuzhno-Sakhalinsk, Russian Federation

e-mail: yu_p_k@mail.ru

Abstract

Purpose. The aim of the work is to study the possibility of real-time tsunami forecasting based on the data from the deep-ocean tsunameters.

Methods and Results. The express method makes it possible to compute in advance the waveforms of the expected tsunami in the ocean, as well as near the coast. Forecasting requires seismological information on the start time and coordinates of the earthquake epicenter only, and also the data from one deep-ocean tsunameter obtained in real time. The data from the deep-ocean tsunameters closest to the tsunami sources with the duration equal to the tsunami first half-period (the first period) were used in the numerical experiments. The results of computing tsumamis for 2007–2015 agree quite well with the tsunami forms recorded at the deep-sea stations in the ocean in different directions from the source. The quality of computations in the article is comparable to the computation quality of the other authors. A tsunami forecast at the given points is possible immediately after receiving the information on passing of the tsunami first period through the deep-sea tsunameter closest to the source.

Conclusions. In contrast to the other methods, no reconstructing of a seismic source neither a giant base of synthetic mareograms is required for the express method. The express method can be used for tsunami forecasting in those areas for which other methods are not applicable (for example, there is no a database of synthetic mareograms), namely the coast of the northwestern Pacific Ocean.

Keywords

tsunami, short-term tsunami forecast, tsunami alarm, false tsunami alarms, reciprocity principle, ocean level, ocean level measurements, tsunami warning service, Pacific Ocean

Acknowledgements

The author is grateful to the reviewers for their useful comments and proposals which were taken into account when finalizing the paper.

Original russian text

Original Russian Text © Yu. P. Korolev, 2023, published in MORSKOY GIDROFIZICHESKIY ZHURNAL, Vol. 39, Iss. 3, pp. 342-358 (2023)

For citation

Korolev, Yu.P., 2023. Evaluation of the Express Method Effectiveness in Short-Term Forecasting on the Examples of the Peruvian (2007) and the Chilean (2010, 2014 and 2015) Tsunamis. Physical Oceanography, 30(3), pp. 315-330. doi:10.29039/1573-160X-2023-3-315-330

DOI

10.29039/1573-160X-2023-3-315-330

References

  1. Frolov, A.V., Martyshchenko, V.A., Kamaev, D.A. and Shershakov, V.M., 2012. Experience of the Russian Tsunami Warning System Updating. Russian Meteorology and Hydrology, 37(6), pp. 357-368. doi:10.3103/S1068373912060015
  2. Whitmore, P.M. and Sokolowski, T.J., 1996. Predicting Tsunami Amplitudes along the North American Coast from Tsunamis Generated in the Northwest Pacific Ocean during Tsunami Warnings. Science of Tsunami Hazards, 14(3), pp. 147-166. Available at: http://tsunamisociety.org/STHVol14N3Y1996.pdf [Accessed: 15 May 2023].
  3. Wei, Y., Cheung, K.F., Curtis, G.D. and McCreery, C.S., 2003. Inverse Algorithm for Tsunami Forecasts. Journal of Waterway, Ports, Coastal, and Ocean Engineering, 129(2), pp. 60-69. doi:10.1061/(ASCE)0733-950x(2003)129:2(60)
  4. González, F.I., Titov, V.V., Avdeev, A.V., Bezhaev, A.Yu., Lavrentiev Jr., M.M. and Marchuk, An.G., 2003. Real-Time Tsunami Forecasting: Challenges and Solutions. In: ICMMG, 2003. Proceedings of the International Conference on Mathematical Methods in Geophysics–2003. Novosibirsk: ICMMG Publisher, pp. 225-228.
  5. Percival, D.B., Denbo, D.W., Eblé, M.C., Giga, E., Mofjeld, H.O., Spillane, M.C., Tang, L. and Titov, V.V., 2011. Extraction of Tsunami Source Coefficients via Inversion of DART® Buoy Data. Natural Hazards, 58(1), pp. 567-590. doi:10.1007/s11069-010-9688-1
  6. Korolev, Yu.P., 2011. An Approximate Method of Short-Term Tsunami Forecast and the Hindcasting of Some Recent Events. Natural Hazards and Earth System Sciences, 11(11), pp. 3081-3091. doi:10.5194/nhess-11-3081-2011
  7. Korolev, Yu.P., 2019. On Opportunity of Short-Term Forecast for Local Tsunamis in the Kuril Islands. Fundamental and Applied Hydrophysics, 12(4), pp. 14-20. doi:10.7868/S2073667319040026 (in Russian).
  8. Korolev, Yu.P. and Korolev, P.Yu., 2020. Short-Term Forecast of Local Tsunamis Based on Data Containing Seismic Noise from Deep-Ocean Stations Closest to the Sources. Geosystems of Transition Zones, 4(4), pp. 447-473. doi:10.30730/gtrz.2020.4.4.447-460.461- 473 (in Russian).
  9. Gusiakov, V.K., 2016. Tsunamis on the Russian Pacific Coast: History and Current Situation. Russian Geology and Geophysics, 57(9), pp. 1259-1268. doi:10.1016/j.rgg.2016.08.011
  10. Gusiakov, V.K., 2011. Relationship of Tsunami Intensity to Source Earthquake Magnitude as Retrieved from Historical Data. Pure and Applied Geophysics, 168(11), pp. 2033-2041. doi:10.1007/s00024-011-0286-2
  11. Korolev, Yu.P. and Loskutov, A.V., 2018. On the Reliable Short-Term Tsunami Forecast. Issues of Risk Analysis, 15(1), pp. 26-33. doi:10.32686/1812-5220-2018-15-1-26-33 (in Russian).
  12. Satake, K., 1987. Inversion of Tsunami Waveforms for the Estimation of a Fault Heterogeneity: Method and Numerical Experiments. Journal of Physics of the Earth, 35(3), pp. 241-254. doi:10.4294/jpe1952.35.241
  13. Titov, V.V., 2009. Tsunami Forecasting. In: E.N. Bernard and A.R. Robinson, eds., 2009. Tsunamis. Cambridge, MA; London, England: Harvard University Press, pp. 367-396.
  14. Gusman, A.R., Tanioka, Y., MacInnes, B.T. and Tsushima, H., 2014. A Methodology for Near-Field Tsunami Inundation Forecasting: Application to the 2011 Tohoku Tsunami. Journal of Geophysical Research: Solid Earth, 119(11), pp. 8186-8206. doi:10.1002/2014JB010958
  15. Hossen, M.J., Cummins, P.R., Roberts, S.G. and Allgeyer, S., 2015. Time Reversal Imaging of the Tsunami Source. Pure and Applied Geophysics, 172(3-4), pp. 969-984. doi:10.1007/s00024-014-1014-5
  16. Mulia, I.E. and Asano, T., 2016. Initial Tsunami Source Estimation by Inversion with an Intelligent Selection of Model Parameters and Time Delays. Journal of Geophysical Research: Oceans, 121(1), pp. 441-456. doi:10.1002/2015JC010877
  17. Mulia, I.E., Gusman, A.R. and Satake K., 2017. Optimal Design for Placements of Tsunami Observing Systems to Accurately Characterize the Inducing Earthquake. Geophysical Research Letters, 44(24), pp. 12106-12115. doi:10.1002/2017GL075791
  18. Navarrete, P., Cienfuegos, R., Satake, K., Wang, Y., Urrutia, A., Benavente, R., Catalán, P.A., Crempien, J. and Mulia, I., 2020. Sea Surface Network Optimization for Tsunami Forecasting in the Near Field: Application to the 2015 Illapel Earthquake. Geophysical Journal International, 221(3), pp. 1640-1650. doi:10.1093/gji/ggaa098
  19. Wang, Y., Maeda, T., Satake, K., Heidarzadeh, M., Su, H., Sheehan, A.F. and Gusman, A.R., 2019. Tsunami Data Assimilation without a Dense Observation Network. Geophysical Research Letters, 46(4), pp. 2045-2053. doi:10.1029/2018GL080930
  20. Wang, Y., Satake, K., Cienfuegos, R., Quiroz, M. and Navarrete, P., 2019. Far-Field Tsunami Data Assimilation for the 2015 Illapel Earthquake. Geophysical Journal International, 219(1), pp. 514-521. doi:10.1093/gji/ggz309
  21. Shevchenko, G.V., Ivel’skaya, T.N., Kovalev, P.D., Kovalev, D.P., Kurkin, A.A., Levin, B.V., Likhacheva, O.N., Chernov, A.G. and Shishkin, A.A., 2011. New Data about Tsunami Evidence on Russia’s Pacific Coast Based on Instrumental Measurements for 2009-2010. Doklady Earth Sciences, 438(2), pp. 893-898. doi:10.1134/S1028334X11060341
  22. Korolev, Y.P. and Khramushin, V.N., 2016. Short-Term Forecast of Tsunami Occurred on April 1, 2014 on the Kuril Islands Coast. Russian Meteorology and Hydrology, 41(4), pp. 293-298. doi:10.3103/S1068373916040099
  23. Okal, E.A., 2015. The Quest for Wisdom: Lessons from 17 Tsunamis, 2004–2014. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 373(2053), 20140370. doi:10.1098/rsta.2014.0370
  24. Smith, W.H.F. and Sandwell, D.T., 1994. Bathymetric Prediction from Dense Satellite Altimetry and Sparse Shipboard Bathymetry. Journal of Geophysical Research: Solid Earth, 99(B11), pp. 21803-21824. doi:10.1029/94JB00988
  25. Smith, W.H.F. and Sandwell, D.T., 1997. Global Sea Floor Topography from Satellite Altimetry and Ship Depth Soundings. Science, 277(5334), pp. 1956-1962. doi:10.1126/science.277.5334.1956
  26. Hébert, H., Reymond, D., Krien, Y., Vergoz, J., Schindelé, F., Roger, J. and Loevenbruck, A., 2009. The 15 August 2007 Peru Earthquake and Tsunami: Influence of the Source Characteristics on the Tsunami Heights. Pure and Applied Geophysics, 166(1-2), pp. 211-232. doi:10.1007/s00024-008-0439-0
  27. Wei, Y., Bernard, E.N., Tang, L., Weiss, R., Titov, V.V., Moore, C., Spillane, M., Hopkins, M. and Kânoğlu, U., 2008. Real-Time Experimental Forecast of the Peruvian Tsunami of August 2007 for U.S. Coastlines. Geophysical Research Letters, 35(4), L04609. doi:10.1029/2007GL032250
  28. Yoshimoto, M., Watada, S., Fujii, Y. and Satake, K., 2016. Source Estimate and Tsunami Forecast from Far-Field Deep-Ocean Tsunami Waveforms – The 27 February 2010 Mw 8.8 Maule Earthquake. Geophysical Research Letters, 43(2), pp. 659-665. doi:10.1002/2015GL067181
  29. An, C., Sepúlveda, I. and Liu, P.L.-F., 2014. Tsunami Source and Its Validation of the 2014 Iquique, Chile, Earthquake. Geophysical Research Letters, 41(11), pp. 3988-3994. doi:10.1002/2014GL060567
  30. Gusman, A.R., Murotani, S., Satake, K., Heidarzadeh, M., Gunawan, E., Watada, S. and Schurr, B., 2015. Fault Slip Distribution of the 2014 Iquique, Chile, Earthquake Estimated from Ocean-Wide Tsunami Waveforms and GPS Data. Geophysical Research Letters, 42(4), pp. 1053-1060. doi:10.1002/2014GL062604
  31. Heidarzadeh, M., Satake, K., Murotani, S., Gusman, A.R. and Watada, S., 2015. Deep-Water Characteristics of the Trans-Pacific Tsunami from the 1 April 2014 Mw 8.2 Iquique, Chile Earthquake. Pure and Applied Geophysics, 172(3-4) pp. 719-730. doi:10.1007/s00024-014- 0983-8
  32. Tang, L., Titov, V.V., Moore, C. and Wei, Y., 2017. Real-Time Assessment of the 16 September 2015 Chile Tsunami and Implications for Near-Field Forecast. In: C. Braitenberg and A. B. Rabinovich, eds., 2017. The Chile-2015 (Illapel) Earthquake and Tsunami. Cham: Birkhäuser, pp. 267-285. doi:10.1007/978-3-319-57822-4_19
  33. Lavrentiev, M., Lysakov, K., Marchuk, A., Oblaukhov, K. and Shadrin, M., 2019. Fast Evaluation of Tsunami Waves Heights around Kamchatka and Kuril Islands. Science of Tsunami Hazards, 38(1), pp. 1-13. Available at: http://www.tsunamisociety.org/STHVol38N1Y2019.pdf [Accessed: 25 May 2022].

Download the article (PDF)