Inter-model analysis of tsunami-induced coastal currents
Date of Original Version
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.
Lynett, Patrick J., Kara Gately, Rick Wilson, Luis Montoya, Diego Arcas, Betul Aytore, Yefei Bai, Jeremy D. Bricker, Manuel J. Castro, Kwok Fai Cheung, C. G. David, Gozde G. Dogan, Cipriano Escalante, José Manuel González-Vida, Stephan T. Grilli, Troy W. Heitmann, Juan Horrillo, Utku Kânoğlu, Rozita Kian, James T. Kirby, Wenwen Li, Jorge Macías, Dmitry J. Nicolsky, Sergio Ortega, Alyssa Pampell-Manis, Yong Sung Park, Volker Roeber, Naeimeh Sharghivand, and Michael Shelby. "Inter-model analysis of tsunami-induced coastal currents." Ocean Modelling 114, (2017): 14-32. doi:10.1016/j.ocemod.2017.04.003.