Observations and modelling of the travel time delay and leading negative phase of the 16 September 2015 Illapel, Chile tsunami

Peitao Wang Zhiyuan Ren Lining Sun Jingming Hou Zongchen Wang Ye Yuan Fujiang Yu

Peitao Wang, Zhiyuan Ren, Lining Sun, Jingming Hou, Zongchen Wang, Ye Yuan, Fujiang Yu. Observations and modelling of the travel time delay and leading negative phase of the 16 September 2015 Illapel, Chile tsunami[J]. Acta Oceanologica Sinica. doi: 10.1007/s13131-021-1830-2
Citation: Peitao Wang, Zhiyuan Ren, Lining Sun, Jingming Hou, Zongchen Wang, Ye Yuan, Fujiang Yu. Observations and modelling of the travel time delay and leading negative phase of the 16 September 2015 Illapel, Chile tsunami[J]. Acta Oceanologica Sinica. doi: 10.1007/s13131-021-1830-2

doi: 10.1007/s13131-021-1830-2

Observations and modelling of the travel time delay and leading negative phase of the 16 September 2015 Illapel, Chile tsunami

Funds: The National Key Research and Development Program of China under contract Nos 2018YFC1407000 and 2016YFC1401500; the National Natural Science Foundation of China under contract Nos 41806045 and 51579090.
More Information
    Corresponding author: E-mail: wpt@nmefc.cn
  • Generally, tsunami travel time is defined as the time required for the first tsunami wave to propagate from its source to a given point.
    • 关键词:
    •  / 
    •  / 
    •  / 
    •  / 
    •  / 
    •  / 
    •  / 
    •  
    Generally, tsunami travel time is defined as the time required for the first tsunami wave to propagate from its source to a given point.
  • Figure  1.  General map of calculation region showing the locations of 50 selected observatories used in this study and the distribution of seafloor vertical deformation generated by the 2015 Mw 8.3 Illapel earthquake. a. Yellow star represents the epicenter. Solid circles and triangles indicate the locations of DART stations and tide gauges respectively. Detailed information of near-field tide gauges in the rectangular box was listed in Table 1. b. The seafloor vertical displacement was based on US Geological Survey finite fault source model. Black solid lines show the uplift contours with 0.2-m intervals while dashed lines show subsidence contours with 0.05-m intervals.

    Figure  2.  The 16 September 2015 Chile tsunami recorded by tide gauges at 22 near-field sites and 7 far-field sites. The red shaded areas are the leading negative phase marking the arrival of the tsunami waves.

    Figure  3.  Tsunami waveform from 2015 Illapel tsunami recorded on DART stations across the Pacific Ocean. The red shaded areas are the leading negative phase that preceded the arrival of the main tsunami.

    Figure  4.  The relationship between the distance from the source and travel time. The black circles indicate the data available from DART observations for the 2015 Illapel, Chile tsunami.

    Figure  5.  Contours of the amplitude ratio (%) of the LNP to the first frontal crest wave determined from near-field and far-field records across the Pacific Ocean. The solid line with red arrow represents the normal direction to the fault strike. Yellow star represents the epicenter. Solid circles and triangles indicate the locations of DART stations and tide gauges respectively.

    Figure  6.  Distribution of maximum simulated tsunami amplitude guided by seafloor topography and fault strike for the 2015 Illaple tsunami. Yellow star represents the epicenter. Solid circles indicate the locations of DART stations.

    Figure  7.  Comparison of simulated waveforms with the observed DART records (black lines) for the 2015 Illapel tsunami. The blue lines indicate simulated tsunami by solving the LSW; the green lines indicate simulated tsunami with the effects of the elastic loading; and the red lines represent simulated tsunami with the coupling effects of elastic loading, seawater density stratification and wave dispersion.

    Figure  8.  Comparison of simulated waveforms with the observed DART records (black lines) for the 2015 Illapel tsunami. The blue lines indicate simulated tsunami by solving the LSW. The green lines indicate simulated tsunami with the effect of the seawater density stratification. The red lines represent simulated tsunami with the wave dispersion.

    Figure  9.  Comparison of the LSW simulated tsunami propagation snapshots with corrected LSW simulations in the Pacific Ocean at 4 h, 15 h and 21 h after the earthquake. Column a shows the tsunami wavefields simulated by solving the LSW model, Column b shows the corrected tsunami wavefields simulated by taking into account the effect seawater density stratification, Column c shows the simulated tsunami wavefields with a correction for wave dispersion, Column d shows the simulated tsunami wavefields with SAL correction, Column e represents the simulated tsunami wavefield with coupled ECD correction, and Column f depicts the snapshots display area of tsunami propagation at corresponding moment. The positions of black arrow indicate the LNP arriving.

    Figure  10.  The travel time delays as function of the tsunami travel time across the Pacific Ocean (a), and the relationship between the ratio of Td to Tc and travel time based on available deep-ocean data (b). The black circles in a are the available DART observed travel time delays relative to the numerically simulated long waves.

    Figure  11.  Evaluation the impact of different correction schemes for improving tsunami travel time delay. a. Comparison of travel time delays between observed waveforms relative to the LSW simulations and corrected travel time delay at each DART station. b. The travel time delay differences between improved travel time delay and Td as functions of travel time (Tc).

    Figure  12.  The contribution rate for improving travel time delay using different correction schemes. Comparison the impact of SAL, seawater density stratification due to compressibility, physical dispersion and the coupling effects (ECD) on tsunami travel time delay corrections.

    Figure  13.  Percent differences of simulated maximum amplitude for the 2015 Chilean tsunami between with and without corrected models. a. Percent change between the LSW results and the corrected LSW simulations by coupling the seawater density stratification due to compressibility effect, b. percent change between the LSW results and the corrected LSW simulations by coupling the SAL effect, c. percent difference between the LSW results and the corrected LSW taking into account the effect of wave dispersion, and d. percent change between the LSW and the corrected LSW that includes the effects of the SAL, stratification and physical dispersion.

    Figure  14.  Tsunami arrival time differences (Δt) between estimated corrected LSW simulations and LSW solvers. a. arrival time difference between the simulated tsunami that take into account dispersion effects and the LSW results, b. arrival time difference between the simulated tsunami with a correction for elasticity of solid Earth and the LSW results, c. arrival time difference between the simulation that take into account seawater stratification and the LSW results, and d. arrival time difference between the simulation that take into account the effects of ECD and the LSW results.

    Table  1.   DART stations and tide gauges that recorded the leading negative phase during the 2015 Illapel, Chile tsunami

    No. Station Location (DART)CoordinatesSampling interval/min SNR3)/dB
    Institution or country (tide gauges)LatitudeLongitude
    121414184 n mile1) SW of Adak, Alaska, USA48.948°N178.247°E 12)20
    221415175 n mile South of Attu, Alaska, USA50.183°N171.847°E123
    321416240 n mile SE of Kamchatka Peninsula, Russia48.040°N163.490°E121
    432411710 n mile WSW of Panama City, Panama4.995°N90.850°W115
    532412630 n mile SW of Lima, Peru17.979°S86.369°W133
    643412240 n mile SW of Manzanillo, Mexico16.026°N106.997°W120
    743413360 n mile SSW of Acapulco, Mexico10.842°N100.137°W121
    846403230 n mile SE of Shumagin Island, Alaska, USA52.650°N156.946°W123
    946404230 n mile West of Astoria, Oregon, USA45.853°N128.775°W118
    1046407210 n mile West of Coos Bay, Oregon, USA42.665°N128.806°W116
    1146408212 n mile South of Umnak Island, Alaska, USA49.668°N169.888°W123
    1246409240 n mile SE of Kodiak, Alaska, USA55.300°N148.515°W124
    1346411150 n mile West of Mendocino Bay, California, USA39.342°N127.021°W119
    1446413243 n mile SSE of Adak, Alaska, USA47.999°N174.227°W125
    1551407140 n mile SE of Honolulu, Hawaii, USA19.553°N156.546°W121
    1651425370 n mile NW of Apia, Samoa9.510°S176.241°W127
    1751426400 n mile SE of Kingdom of Tonga22.974°S168.139°W126
    1852401610 n mile ENE of Saipan, Northern Mariana Islands19.261°N155.754°E122
    1952402540 n mile ESE of Saipan, Northern Mariana Islands11.869°N154.039°E118
    2052403345 n mile North of Manus Island, PNG4.020°N145.520°E117
    2152404760 n mile NE of Manila, Philippines20.790°N132.340°E119
    22CoquimboSHOA Chile29.950°S71.335°W139
    23QuinteroSHOA, Chile32.775°S71.525°W133
    24ValparaisoSHOA, Chile33.027°S71.626°W130
    25HuascoSHOA, Chile28.461°S71.224°W128
    26San AntonioSHOA, Chile33.582°S71.618°W129
    27CalderaSHOA, Chile27.065°S70.825°W128
    28BucalemuSHOA, Chile34.639°S72.046°W126
    29PaposoSHOA, Chile25.009°S70.469°W116
    30ConstitucionSHOA, Chile35.356°S72.458°W123
    31ChanaralSHOA, Chile26.352°S70.634°W125
    32TaltalSHOA, Chile25.408°S70.492°W118
    33LebuSHOA, Chile37.594°S73.664°W120
    34CoronelSHOA, Chile37.029°S73.152°W121
    35QuiriquinaSHOA, Chile36.636°S73.057°W122
    36TalcahuanoSHOA, Chile36.701°S73.106°W123
    37MejillonesSHOA, Chile23.098°S70.451°W117
    38AntofagastaSHOA, Chile23.653°S70.404°W121
    39PatacheSHOA, Chile20.803°S70.198°W116
    40CorralSHOA, Chile39.887°S73.427°W118
    41IquiqueSHOA, Chile20.205°S70.148°W115
    42PisaguaSHOA, Chile19.596°S70.216°W114
    43AncudSHOA, Chile41.867°S73.833°W114
    44CallaoDHN, Peru12.069°S77.167°W115
    45ChathamLINZ, New Zealand44.025°S176.369°W115
    46East CapeLINZ, New Zealand37.550°S178.159°E118
    47Arena coveNOS/NOAA, USA38.913°N123.705°W118
    48PagoNOS/NOAA, USA14.277°S170.691°E123
    49Great BarrierLINZ, New Zealand36.189°S175.489°E120
    50Sand PointNOS/NOAA, USA55.337°N160.502°W112
    Notes: 1)1 n mile = 1.852 km. 2)“Event-mode” DART data. 3)${\rm {SNR} } = 20 {\log _{10} }\!\left({\dfrac{ { {A_{\rm{signal} } } }}{ { {A_{\rm{noise} } } } } } \right)$, ${A_{\rm{signal}}}$: maximum amplitude of signal, ${A_{\rm{noise}}}$: maximum amplitude of Noise. PNG: Papua New Guinea, SHOA: Servicio Hidrográfico y Oceanográfico de la Armada de Chile, LINZ: Land Information New Zealand, NOS/NOAA: National Oceanic and Atmospheric Administration's National Ocean Service.
    下载: 导出CSV

    Table  2.   Statistical characteristics of the 2015 Illapel, Chile tsunami estimated from DART Buoy records and tide gauge data

    StationDistance1)/
    km
    Azimuth2)/
    (°)
    LNPFirst frontal
    crest wave
    Max. wavePeak periods
    /min
    $\left| {{\zeta _1}/{\zeta _2}} \right|$
    ${T^{{\rm{3)}}}}$/h$\zeta _{\rm{1}}^{{\rm{4)}}}$/cm${\tau ^{5)}}$/min$\zeta _{\rm{2}}^{6)}$/cm$\zeta _{\rm{3}}^{7)}$/cmSignNo. of the
    max. wave
    324122 044391.85−0.79546.826.82(+)175, 40, 1412%
    324114 499225.80−0.82241.821.82(+)175, 28, 945%
    434135 549307.29−0.62301.412.22(−)344, 28, 644%
    434126 435338.34−0.62522.022.66(+)241, 18, 930%
    514269 17810512.22−0.44161.362.73(−)487, 38, 1732%
    464119 6743213.44−0.56271.391.39(+)144, 28, 1740%
    4640710 0423114.00−0.54281.321.32(+)150, 29, 1741%
    4640410 2912914.61−0.47281.091.09(+)171, 31, 1743%
    5140710 5776414.00−0.61311.861.86(+)162, 1833%
    5142510 7129914.21−0.44320.724.25(−)262, 33, 1861%
    4640912 0262916.49−0.47362.052.05(+)171, 38, 1323%
    4640312 3843416.67−0.57302.042.04(+)162, 33, 1528%
    4640813 1114017.34−0.57242.142.14(+)131, 18, 1327%
    4641313 3654317.12−0.37471.892.59(−)262, 41, 1320%
    2141413 9284318.05−0.54311.371.99(−)266, 31, 1539%
    2141514 4044218.63−0.47341.692.42(+)366, 31, 1328%
    5240214 7649719.67−0.42520.911.63(−)281, 33, 1446%
    5240314 98711321.39−0.33280.331.16(+)433, 15100%
    5240115 0038718.60−0.22481.461.46(+)166, 44, 1415%
    2141615 5044518.95−0.52490.922.17(+)566, 44, 1757%
    5240417 25310322.59−0.81651.281.99(−)281, 31, 1541%
    Quintero1721480−8.1418136181(+)231, 146%
    Valparaiso1891560−9.8323117173(+)3358%
    Coquimbo221420−24.182193466(+)433, 1726%
    San Antonio2441630−6.603065108(−)447, 1810%
    Bucalemu3451760−4.62404585(−)838, 1810%
    Huasco373290−3.75274780(+)531, 138%
    Constitucion4211760−4.375050110(+)362, 44, 189%
    Caldera532270.20−4.26343490(+)1031, 1513%
    Quiriquina5631700.77−5.48342478(−)387, 27, 823%
    Talcahuano5711690.60−7.655443115(−)387, 31, 1718%
    Coronel6081690.60−5.61422562(+)5115, 4422%
    Chanaral613260.40−4.452442119(+)33111%
    Lebu6751660.38−3.03452232(+)344, 1514%
    Taltal717250.47−3.37262033(+)631, 18, 917%
    Paposo761240.32−2.95361919(+)166, 44, 33, 1716%
    Antofagasta908220.70−2.41241846(−)44413%
    Corral9271691.20−3.47472432(+)487, 3314%
    Mejillones967210.80−3.44241429(−)241, 25, 1725%
    Ancud1 1491681.63−3.7448616(−)471, 1862%
    Patache1 223191.10−3.72301233(−)24731%
    Iquique1 289190.80−4.21481129(+)744, 25, 1538%
    Pisagua1 354180.97−2.78501020(+)747, 1327%
    Callao2 21762.88−6.21301959(+)947, 31, 1332%
    Chatham8 60112712.35−8.14242948(+)476, 35, 1928%
    East Cape9 38512412.85−0.9726814(−)52012%
    Arena Cove9 4453013.48−1.2324610(−)681, 33, 1521%
    Great Barrier9 66612413.62−2.06241220(+)538, 1517%
    Pago11 55711013.73−4.87121347(+)518, 937%
    Sand Point12 7133518.17−2.1528919(+)841, 25, 1624%
    Average33Average72, 30, 1840%
    Notes: 1)The distance of every station to the epicenter based on spherical earth system. 2)The angles of the station in relation to fault strike. 3)Travel time of the LNP is in hours after the earthquake. 4)The maximum amplitude of the LNP. 5)The duration of the LNP. 6)The maximum amplitude of the first frontal crest wave. The first frontal crest wave usually is defined as the crest of the first tsunami wave. In general, it is the max over the first zero-crossing wave period since tsunami arrived. 7)The maximum tsunami amplitude records.
    下载: 导出CSV

    Table  3.   Summary of the observed travel time and the travel time delays for the 2015 Chilean tsunamis at DART buoy stations

    StationDistance1)/kmDepth/mTc2)/hTd3)/minCorrections of the travel time delay/min
    SALDensity stratificationWave dispersionECD4)
    324122 0444 3202.874.54.33.83.52.3
    324114 4993 2296.583.62.61.82.10.0
    434135 5493 7407.893.92.81.82.5−0.75)
    434126 4353 1429.325.13.32.03.5−0.75)
    514269 1785 65912.6111.49.07.610.74.1
    464119 6744 32514.009.57.65.77.81.8
    4640710 0423 30014.598.46.14.56.70.0
    4640410 2913 73815.178.36.24.36.60.0
    5140710 5774 73714.6412.510.48.210.63.8
    5142510 7124 88914.8713.711.19.412.45.0
    4640912 0264 19417.2410.37.75.48.30.0
    4640312 3844 51317.3111.99.37.110.21.7
    4640813 1115 37217.8713.29.97.611.41.9
    4641313 3655 58318.0414.411.78.812.53.1
    2141413 9285 47918.6814.411.68.612.52.7
    2141514 4044 85519.3318.015.012.016.46.2
    5240214 7645 88620.7121.317.615.318.28.2
    5240314 9874 46621.9220.917.714.517.67.7
    5240115 0035 57020.6218.616.012.818.05.4
    2141615 5045 83119.8815.512.49.313.42.6
    5240417 2535 86423.9621.917.814.918.26.3
    Average contribution rate21%39%18%78%
    Notes: 1)The distance of every station to the epicenter based on spherical earth system. 2)Tc indicates travel time of the first frontal crest wave is in hours after the earthquake. 3)Td indicates travel time of the first frontal crest wave delay relative to linear long waves is in minutes. 4)Improved corrections with self-attraction and loading due to elasticity loading, seawater density stratification due to compressibility and dispersion effects. 5)Negative value represent the first frontal crest wave arrive earlier than improved phase corrections results.
    下载: 导出CSV
  • [1] Abdolali A, Kadri U, Kirby J T. 2019. Effect of water compressibility, sea-floor elasticity, and field gravitational potential on tsunami phase speed. Scientific Reports, 9(1): 16874. doi: 10.1038/s41598-019-52475-0
    [2] Abdolali A, Kirby J T. 2017. Role of compressibility on tsunami propagation. Journal of Geophysical Research: Oceans, 122(12): 9780–9794. doi: 10.1002/2017JC013054
    [3] Allgeyer S, Cummins P. 2014. Numerical tsunami simulation including elastic loading and seawater density stratification. Geophysical Research Letters, 41(7): 2368–2375. doi: 10.1002/2014GL059348
    [4] An Chao, Liu P L F. 2016. Analytical solutions for estimating tsunami propagation speeds. Coastal Engineering, 117: 44–56. doi: 10.1016/j.coastaleng.2016.07.006
    [5] Aránguiz R, González G, González J, et al. 2016. The 16 September 2015 Chile tsunami from the post-tsunami survey and numerical modeling perspectives. Pure and Applied Geophysics, 173(2): 333–348. doi: 10.1007/s00024-015-1225-4
    [6] Baba T, Allgeyer S, Hossen J, et al. 2017. Accurate numerical simulation of the far-field tsunami caused by the 2011 Tohoku earthquake, including the effects of Boussinesq dispersion, seawater density stratification, elastic loading, and gravitational potential change. Ocean Modelling, 111: 46–54. doi: 10.1016/j.ocemod.2017.01.002
    [7] Baba T, Ando K, Matsuoka D, et al. 2016. Large-scale, high-speed tsunami prediction for the great Nankai Trough earthquake on the K computer. The International Journal of High Performance Computing Applications, 30(1): 71–84. doi: 10.1177/1094342015584090
    [8] Baba T, Cummins P R, Thio H K, et al. 2009. Validation and joint inversion of teleseismic waveforms for earthquake source models using deep ocean bottom pressure records: A case study of the 2006 Kuril megathrust earthquake. Pure and Applied Geophysics, 166(1-2): 55–76. doi: 10.1007/s00024-008-0438-1
    [9] Baba T, Takahashi N, Kaneda Y, et al. 2015. Parallel implementation of dispersive tsunami wave modeling with a nesting algorithm for the 2011 Tohoku tsunami. Pure and Applied Geophysics, 172(12): 3455–3472. doi: 10.1007/s00024-015-1049-2
    [10] Barazangi M, Isacks B L. 1976. Spatial distribution of earthquakes and subduction of the Nazca plate beneath South America. Geology, 4(11): 686–692. doi: 10.1130/0091-7613(1976)4<686:SDOEAS>2.0.CO;2
    [11] Berger M J, George D L, Leveque R J, et al. 2011. The GeoClaw software for depth-averaged flows with adaptive refinement. Advances in Water Resources, 34(9): 1195–1206. doi: 10.1016/j.advwatres.2011.02.016
    [12] Contreras-López M, Winckler, P, Sepúlveda I, et al. 2016. Field survey of the 2015 Chile tsunami with emphasis on coastal wetland and conservation areas. Pure and Applied Geophysics, 173(2): 349–367. doi: 10.1007/s00024-015-1235-2
    [13] DeMets C, Gordon R G, Argus D F, et al. 1994. Effect of recent revisions to the geomagnetic reversal time scale on estimates of current plate motions. Geophysical Research Letters, 21(20): 2191–2194. doi: 10.1029/94GL02118
    [14] Eblé M C, Mungov G T, Rabinovich A B. 2015. On the leading negative phase of major 2010-2014 tsunamis. Pure and Applied Geophysics, 172(12): 3493–3508. doi: 10.1007/s00024-015-1127-5
    [15] Heidarzadeh M, Murotani S, Satake K, et al. 2016. Source model of the 16 September 2015 Illapel, Chile, Mw8.4 earthquake based on teleseismic and tsunami data. Geophysical Research Letters, 43(2): 643–650. doi: 10.1002/2015GL067297
    [16] Heidarzadeh M, Satake K. 2013. Waveform and spectral analyses of the 2011 Japan tsunami records on tide gauge and DART stations across the Pacific Ocean. Pure and Applied Geophysics, 170(6−8): 1275–1293. doi: 10.1007/s00024-012-0558-5
    [17] Heidarzadeh M, Satake K. 2014. The El Salvador and Philippines tsunamis of August 2012: insights from sea level data analysis and numerical modeling. Pure and Applied Geophysics, 171(12): 3437–3455. doi: 10.1007/s00024-014-0790-2
    [18] Heidarzadeh M, Satake K, Murotani S, et al. 2015. Deep-water characteristics of the trans-Pacific tsunami from the 1 April 2014 Mw8.2 Iquique, Chile earthquake. Pure and Applied Geophysics, 172(3−4): 719–730. doi: 10.1007/s00024-014-0983-8
    [19] Heidarzadeh M, Satake K, Takagawa T, et al. 2018. A comparative study of far-field tsunami amplitudes and ocean-wide propagation properties: insight from major trans-Pacific tsunamis of 2010−2015. Geophysical Journal International, 215(1): 22–36. doi: 10.1093/gji/ggy265
    [20] Ho T C, Satake K, Watada S. 2017. Improved phase corrections for transoceanic tsunami data in spatial and temporal source estimation: application to the 2011 Tohoku earthquake. Journal of Geophysical Research: Solid Earth, 122(12): 10155–10175. doi: 10.1002/2017JB015070
    [21] Inazu D, Saito T. 2013. Simulation of distant tsunami propagation with a radial loading deformation effect. Earth Planets Space, 65(8): 835–842. doi: 10.5047/eps.2013.03.010
    [22] Jakeman J D, Nielsen O M, Putten K V, et al. 2010. Towards spatially distributed quantitative assessment of tsunami inundation models. Ocean Dynamics, 60(5): 1115–1138. doi: 10.1007/s10236-010-0312-4
    [23] Ji Chen, Wald D J, Helmberger D V. 2002. Source description of the 1999 hector mine, California, earthquake, part I: wavelet domain inversion theory and resolution analysis. Bulletin of the Seismological Society of America, 92(4): 1192–1207. doi: 10.1785/0120000916
    [24] Kajiura K. 1963. The leading wave of a tsunami. Bulletin of the Earthquake Research Institute, University of Tokyo, 41(3): 535–571
    [25] Kato T, Terada Y, Nishimura H, et al. 2011. Tsunami records due to the 2010 Chile Earthquake observed by GPS buoys established along the Pacific coast of Japan. Earth, Planets and Space, 63(6): e5–e8. doi: 10.5047/eps.2011.05.001
    [26] Kirby J T, Shi Fengyan, Tehranirad B, et al. 2013. Dispersive tsunami waves in the ocean: model equations and sensitivity to dispersion and Coriolis effects. Ocean Modelling, 62: 39–55. doi: 10.1016/j.ocemod.2012.11.009
    [27] Li Bo, Ghosh A. 2016. Imaging rupture process of the 2015 Mw 8.3 Illapel earthquake using the US seismic array. Pure and Applied Geophysics, 173(7): 2245–2255. doi: 10.1007/s00024-016-1323-y
    [28] Lu W F, Jiang Y W, Lin J. 2013. Modeling propagation of 2011 Honshu tsunami. Engineering Applications of Computational Fluid Mechanics, 7(4): 507–518. doi: 10.1080/19942060.2013.11015489
    [29] Okada Y. 1985. Surface deformation due to shear and tensile faults in a half-space. Bulletin of the Seismological Society of America, 75(4): 1135–1154. doi: 10.1785/BSSA0750041135
    [30] Poupardin P, Heinrich P, Hébert H, et al. 2018. Traveltime delay relative to the maximum energy of the wave train for dispersive tsunamis propagating across the Pacific Ocean: the case of 2010 and 2015 Chilean Tsunamis. Geophysical Journal International, 214(3): 1538–1555. doi: 10.1093/gji/ggy200
    [31] Prastowo T, Cholifah L, Madlazim. 2018. Analysis of travel time delay for large tsunamis across the pacific and Indian Oceans. Science of Tsunami Hazards, 37(4): 195–212
    [32] Rabinovich A B, Candella R N, Thomson R E. 2013a. The open ocean energy decay of three recent trans-Pacific tsunamis. Geophysical Research Letters, 40(12): 3157–3162. doi: 10.1002/grl.50625
    [33] Rabinovich A B, Thomson R E. 2007. The 26 December 2004 Sumatra tsunami: analysis of tide gauge data from the World Ocean Part 1. Indian Ocean and South Africa. Pure and Applied Geophysics, 164(2): 261–308. doi: 10.1007/s00024-006-0164-5
    [34] Rabinovich A B, Thomson R E, Fine I V. 2013b. The 2010 Chilean tsunami off the west coast of Canada and the northwest coast of the United States. Pure and Applied Geophysics, 170(9-10): 1529–1565. doi: 10.1007/s00024-012-0541-1
    [35] Rabinovich A B, Titov V V, Moore C W, et al. 2017. The 2004 Sumatra tsunami in the southeastern Pacific Ocean: New global insight from observations and modeling. Journal of Geophysical Research: Oceans, 122(10): 7992–8019. doi: 10.1002/2017JC013078
    [36] Rabinovich A B, Woodworth P L, Titov V V. 2011. Deep-sea observations and modeling of the 2004 Sumatra tsunami in Drake Passage. Geophysical Research Letters, 38(16): L16604. doi: 10.1029/2011GL048305
    [37] Roberts S G, Nielsen O M, Gray D, et al. 2015. ANUGA User Manual, Release 2.0. Symonston: Geoscience Australia, https://www.researchgate.net/publication/318511561_ANUGA_User_Manual_Release_20[2015-05-19/2020-10-01]
    [38] Roberts S G, Nielsen O M, Jakeman J. 2008. Simulation of tsunami and flash floods. In: Bock H G, Kostina E, Phu H X, et al, eds. Modeling, Simulation and Optimization of Complex Processes. Berlin, Heidelberg: Springer, doi: 10.1007/978-3-540-79409-7_35
    [39] Röbke B R, Vött A. 2017. The tsunami phenomenon. Progress in Oceanography, 159: 296–322. doi: 10.1016/j.pocean.2017.09.003
    [40] Satake K, Heidarzadeh M. 2017. A review of source models of the 2015 Illapel, Chile earthquake and insights from tsunami data. Pure and Applied Geophysics, 174(1): 1–9. doi: 10.1007/s00024-016-1450-5
    [41] Shan Di, Wang Peitao, Ren Zhiyuan, et al. 2017. Application and evaluation of the 16 September 2015 Illapel, Chile Mw8.3 earthquake finite fault rupture model from numerical simulation. Haiyang Xuebao (in Chinese), 39(11): 49–60. doi: 10.3969/j.issn.0253-4193.2017.11.005
    [42] Tang Liujuan, Titov V V, Moore C, et al. 2016. Real-time assessment of the 16 September 2015 Chile tsunami and implications for near-Field forecast. Pure and Applied Geophysics, 173(2): 369–387. doi: 10.1007/s00024-015-1226-3
    [43] 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. doi: 10.1061/(ASCE)0733-950X(1998)124:4(157)
    [44] Tsai V C, Ampuero J P, Kanamori H, et al. 2013. Estimating the effect of earth elasticity and variable water density on tsunami speeds. Geophysical Research Letters, 40(3): 492–496. doi: 10.1002/grl.50147
    [45] Vigny C, Rudloff A, Ruegg J C, et al. 2009. Upper plate deformation measured by GPS in the Coquimbo Gap, Chile. Physics of the Earth and Planetary Interiors, 175(1−2): 86–95. doi: 10.1016/j.pepi.2008.02.013
    [46] Wang Dailin. 2015. An ocean depth-correction method for reducing model errors in tsunami travel time: application to the 2010 Chile and 2011 Tohoku tsunamis. Science of Tsunami Hazards, 34(1): 1–22
    [47] Wang Dailin, Becker N C, Walsh D, et al. 2012. Real-time forecasting of the April 11, 2012 Sumatra tsunami. Geophysical Research Letters, 39(19): L19601. doi: 10.1029/2012GL053081
    [48] Wang Xiaoming, Liu P L F. 2011. An explicit finite difference model for simulating weakly nonlinear and weakly dispersive waves over slowly varying water depth. Coastal Engineering, 58(2): 173–183. doi: 10.1016/j.coastaleng.2010.09.008
    [49] Wang Peitao, Yu Fujiang, Yuan Ye, et al. 2016. Effects of finite fault rupture models of submarine earthquakes on numerical forecasting of near-field tsunami. Chinese Journal Of Geophysics (in Chinese), 59(3): 1030–1045. doi: 10.6038/cjg20160324
    [50] Watada S. 2013. Tsunami speed variations in density-stratified compressible global oceans. Geophysical Research Letters, 40(15): 4001–4006. doi: 10.1002/grl.50785
    [51] Watada S, Kusumoto S, Satake K. 2014. Traveltime delay and initial phase reversal of distant tsunamis coupled with the self-gravitating elastic earth. Journal of Geophysical Research: Solid Earth, 119(5): 4287–4310. doi: 10.1002/2013JB010841
    [52] Wei Yong, Bernard E N, Tang Liujuan, et al. 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
    [53] Wessel P, Smith W H F. 1998. New, improved version of generic mapping tools released. Eos, Transactions American Geophysical Union, 79(47): 579. doi: 10.1029/98EO00426
    [54] Yamazaki Y, Cheung K F, Kowalik Z. 2011. Depth-integrated, non-hydrostatic model with grid-nesting for tsunami generation, propagation, and run-up. International Journal for Numerical Methods in Fluids, 67(12): 2081–2107. doi: 10.1002/fld.2485
    [55] Yamazaki Y, Cheung K F, Lay T. 2013. Modeling of the 2011 Tohoku near-field tsunami from finite-fault inversion of seismic waves. Bulletin of the Seismological Society of America, 103(2B): 1444–1455. doi: 10.1785/0120120103
    [56] Ye Lingling, Lay T, Kanamori H, et al. 2016. Rapidly estimated seismic source parameters for the 16 September 2015 Illapel, Chile Mw8.3 earthquake. Pure and Applied Geophysics, 173(2): 321–332. doi: 10.1007/s00024-015-1202-y
    [57] Zaytsev O, Rabinovich A B, Thomson R E. 2016. A comparative analysis of coastal and open-ocean records of the great Chilean tsunamis of 2010, 2014 and 2015 off the coast of Mexico. Pure and Applied Geophysics, 173(12): 4139–4178. doi: 10.1007/s00024-016-1407-8
    [58] Zaytsev O, Rabinovich A B, Thomson R E. 2017. The 2011 Tohoku tsunami on the coast of Mexico: A case study. Pure and Applied Geophysics, 174(8): 2961–2986. doi: 10.1007/s00024-017-1593-z
  • 加载中
图(14) / 表(3)
计量
  • 文章访问数:  53
  • HTML全文浏览量:  25
  • PDF下载量:  6
  • 被引次数: 0
出版历程
  • 收稿日期:  2020-11-21
  • 录用日期:  2021-02-23
  • 网络出版日期:  2021-08-27

目录

    /

    返回文章
    返回