Tsunami Focusing and Leading Amplitude
Abstract
Tsunamis transform substantially through spatial and temporal spreading from their source region. This substantial spreading might result unique maximum tsunami wave heights which might be attributed to the source configuration, directivity, the waveguide structures of mid-ocean ridges and continental shelves, focusing and defocusing through submarine seamounts, random focusing due to small changes in bathymetry, dispersion, and, most likely, combination of some of these effects. In terms of the maximum tsunami wave height, after Okal and Synolakis (2016 Geophys. J. Int. 204, 719-735), it is clear that dispersion would be one of the reasons to drive the leading wave amplitude in a tsunami wave train. Okal and Synolakis (2016), referring to this phenomenon as sequencing -later waves in the train becoming higher than the leading one, considered Hammack's (1972, Ph.D. Dissertation, Calif. Inst. Tech., 261 pp) formalism, in addition to LeMéhauté and Wang's (1995 Water waves generated by underwater explosion, World Scientific, 367 pp), to evaluate linear dispersive tsunami propagation from a circular plug uplifted on an ocean of constant depth. They identified transition distance, as the second wave being larger, performing parametric study for the radius of the plug and the depth of the ocean. Here, we extend Okal and Synolakis' (2016) analysis to an initial wave field with a finite crest length and, in addition, to a most common tsunami initial wave form of N-wave (Tadepalli and Synolakis, 1994 Proc. R. Soc. A: Math. Phys. Eng. Sci. 445, 99-112). First, we investigate the focusing feature in the leading-depression side, which enhance tsunami wave height as presented by Kanoglu et al. (2013 Proc. R. Soc. A: Math. Phys. Eng. Sci. 469, 20130015). We then discuss the results in terms of leading wave amplitude presenting a parametric study and identify a simple relation for the transition distance. The solution presented here could be used to better analyze dispersive characteristics of shallow water-wave numerical models and for benchmarking, in addition to the benchmark problems in Synolakis et al. (2008 Pure Appl. Geophys. 165(11-12), 2197-2228). This study received funding from project ASTARTE-Assessment Strategy and Risk Reduction for Tsunamis in Europe, a collaborative project Grant 603839, FP7-ENV2013 6.4-3.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2016
- Bibcode:
- 2016AGUFMNH41A1742K
- Keywords:
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- 3225 Numerical approximations and analysis;
- MATHEMATICAL GEOPHYSICSDE: 4332 Disaster resilience;
- NATURAL HAZARDSDE: 4341 Early warning systems;
- NATURAL HAZARDSDE: 4564 Tsunamis and storm surges;
- OCEANOGRAPHY: PHYSICAL