4.6 Article

Inter-model analysis of tsunami-induced coastal currents

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OCEAN MODELLING
卷 114, 期 -, 页码 14-32

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ELSEVIER SCI LTD
DOI: 10.1016/j.ocemod.2017.04.003

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资金

  1. National Tsunami Hazard Mitigation Program (NTHMP)
  2. NTHMP
  3. National Science Foundation
  4. California Geologic Survey
  5. Japan Society for Promotion of Science [15K06224, 16H04414]
  6. National Oceanic and Atmospheric Administration [4657]
  7. project ASTARTE (Assessment, STrategy And Risk Reduction for Tsunamis in Europe) [603839]
  8. 7th FP [ENV.2013.6.4-3]
  9. Grants-in-Aid for Scientific Research [16H04414, 15K06224] Funding Source: KAKEN

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To help produce accurate and consistent maritime hazard products, the National Tsunami Hazard Mitigation Program organized a benchmarking workshop to evaluate the numerical modeling of tsunami currents. Thirteen teams of international researchers, using a set of tsunami models currently utilized for hazard mitigation studies, presented results for a series of benchmarking problems; these results are summarized in this paper. Comparisons focus on physical situations where the currents are shear and separation driven, and are thus de-coupled from the incident tsunami waveform. In general, we find that models of increasing physical complexity provide better accuracy, and that low-order three-dimensional models are superior to high-order two-dimensional models. Inside separation zones and in areas strongly affected by eddies, the magnitude of both model-data errors and inter-model differences can be the same as the magnitude of the mean flow. Thus, we make arguments for the need of an ensemble modeling approach for areas affected by large-scale turbulent eddies, where deterministic simulation may be misleading. As a result of the analyses presented herein, we expect that tsunami modelers now have a better awareness of their ability to accurately capture the physics of tsunami currents, and therefore a better understanding of how to use these simulation tools for hazard assessment and mitigation efforts. (C) 2017 Elsevier Ltd. All rights reserved.

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