The November 15, 2006 Kuril Islands-Generated Tsunami in Crescent City, California

Dengler, Lori; Uslu, Burak; Barberopoulou, A.; Yim, Solomon C.; Kelly, A.

doi:10.1007/978-3-0346-0064-4_3

Cited by 3 publications

(2 citation statements)

References 6 publications

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“…The event generated a tsunami significant in the near field (MacInnes et al 2009) but only modest in the far field (Fujii & Satake 2008). Significant far‐field damage was reported only in the harbour at Crescent City, California, USA, due to a series of late waves reaching a maximum peak‐to‐peak amplitude of ∼1.7 m there (Dengler et al 2009).…”

Section: Resultsmentioning

confidence: 99%

An extension of the E/M0 tsunami earthquake discriminant Θ to regional distances

Ebeling

Okal

2012

Geophysical Journal International

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The ‘slowness’ parameter Θ, the logarithmic ratio of the estimated energy radiated by an earthquake EE to its moment M0, is a robust indicator of tsunami earthquakes when calculated from waveforms recorded at teleseismic epicentral distances (35° < Δ < 80°). However, Θ values calculated from waveforms recorded at regional epicentral distances (5° < Δ < 35°) are unreliable. This is because the necessary use of a differentiable traveltime T(Δ) curve smoothed through transition zone caustic distances leads to the systematic overestimation of EE, and hence of Θ, for waveforms recorded at or near these distances. Using a data set comprised of 67 global oceanic dip‐slip earthquakes occurring in the last 20 yr that includes six recognized tsunami earthquakes, we empirically develop a Θ correction for waveforms recorded at regional epicentral distances. Application of the correction to our data set allows the recovery of Θ values fully consistent with those calculated using only teleseismic waveforms. The incorporation of this correction into existing tsunami warning algorithms has the potential to significantly advance near‐field warning efforts.

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Section: Resultsmentioning

confidence: 99%

An extension of the E/M0 tsunami earthquake discriminant Θ to regional distances

Ebeling

Okal

2012

Geophysical Journal International

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“…Kanamori () defined a “tsunami earthquake” as “an earthquake that produces a large size tsunami relative to the value of its surface wave magnitude ( M s ).” Polet and Kanamori () modified this definition to include only earthquakes that directly cause a regional and/or teleseismic tsunami that is greater in amplitude than would be typically expected from their seismic moment magnitude. This definition excludes seismic events that were followed by tsunamis directly caused by slides or slumps resulting from the original earthquake, as was the case for example for the 1992 Flores earthquake (Hidayat et al, ) and the 1998 Papua New Guinea earthquake (Synolakis et al, ), as well as events that only very locally caused large tsunamis as a result of, for example, focusing effects due bathymetry (e.g., Satake and Kanamori, ) or directivity effects combined with the shape of the coastline (e.g., Dengler et al, ). Examples of tsunami earthquakes include the 1896 Sanriku event near the coast of Japan (Hatori, ), two events near the Kurile Islands: one in 1963 and the other in 1975 (Fukao, ), the 1992 Nicaragua earthquake (Kanamori & Kikuchi, ), the Peru earthquake 4 years later (Heinrich et al, ), the 2006 Java earthquake (Mori et al, ), and the 2010 Mentawai earthquake (Newman et al, ).…”

Section: Tsunami Generation and Propagation: Causes Mechanisms And mentioning

confidence: 99%

Probabilistic Tsunami Hazard Analysis: Multiple Sources and Global Applications

Grezio

Babeyko²,

Baptista

et al. 2017

Reviews of Geophysics

186

163

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Applying probabilistic methods to infrequent but devastating natural events is intrinsically challenging. For tsunami analyses, a suite of geophysical assessments should be in principle evaluated because of the different causes generating tsunamis (earthquakes, landslides, volcanic activity, meteorological events, and asteroid impacts) with varying mean recurrence rates. Probabilistic Tsunami Hazard Analyses (PTHAs) are conducted in different areas of the world at global, regional, and local scales with the aim of understanding tsunami hazard to inform tsunami risk reduction activities. PTHAs enhance knowledge of the potential tsunamigenic threat by estimating the probability of exceeding specific levels of tsunami intensity metrics (e.g., run‐up or maximum inundation heights) within a certain period of time (exposure time) at given locations (target sites); these estimates can be summarized in hazard maps or hazard curves. This discussion presents a broad overview of PTHA, including (i) sources and mechanisms of tsunami generation, emphasizing the variety and complexity of the tsunami sources and their generation mechanisms, (ii) developments in modeling the propagation and impact of tsunami waves, and (iii) statistical procedures for tsunami hazard estimates that include the associated epistemic and aleatoric uncertainties. Key elements in understanding the potential tsunami hazard are discussed, in light of the rapid development of PTHA methods during the last decade and the globally distributed applications, including the importance of considering multiple sources, their relative intensities, probabilities of occurrence, and uncertainties in an integrated and consistent probabilistic framework.

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Strongest tsunamis in the World Ocean and the problem of marine coastal security

Gusiakov

2014

Izv. Atmos. Ocean. Phys.

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The November 15, 2006 Kuril Islands-Generated Tsunami in Crescent City, California

Cited by 3 publications

References 6 publications

An extension of the E/M0 tsunami earthquake discriminant Θ to regional distances

An extension of the E/M0 tsunami earthquake discriminant Θ to regional distances

Probabilistic Tsunami Hazard Analysis: Multiple Sources and Global Applications

Strongest tsunamis in the World Ocean and the problem of marine coastal security

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