Articles | Volume 18, issue 9
https://doi.org/10.5194/nhess-18-2561-2018
https://doi.org/10.5194/nhess-18-2561-2018
Research article
 | 
21 Sep 2018
Research article |  | 21 Sep 2018

Tree-based mesh-refinement GPU-accelerated tsunami simulator for real-time operation

Marlon Arce Acuña and Takayuki Aoki

Related subject area

Sea, Ocean and Coastal Hazards
An interdisciplinary agent-based evacuation model: integrating the natural environment, built environment, and social system for community preparedness and resilience
Chen Chen, Charles Koll, Haizhong Wang, and Michael K. Lindell
Nat. Hazards Earth Syst. Sci., 23, 733–749, https://doi.org/10.5194/nhess-23-733-2023,https://doi.org/10.5194/nhess-23-733-2023, 2023
Short summary
Coastal extreme sea levels in the Caribbean Sea induced by tropical cyclones
Ariadna Martín, Angel Amores, Alejandro Orfila, Tim Toomey, and Marta Marcos
Nat. Hazards Earth Syst. Sci., 23, 587–600, https://doi.org/10.5194/nhess-23-587-2023,https://doi.org/10.5194/nhess-23-587-2023, 2023
Short summary
Characteristics of consecutive tsunamis and resulting tsunami behaviors in southern Taiwan induced by the Hengchun earthquake doublet on 26 December 2006
An-Chi Cheng, Anawat Suppasri, Kwanchai Pakoksung, and Fumihiko Imamura
Nat. Hazards Earth Syst. Sci., 23, 447–479, https://doi.org/10.5194/nhess-23-447-2023,https://doi.org/10.5194/nhess-23-447-2023, 2023
Short summary
Potential tsunami hazard of the southern Vanuatu subduction zone: tectonics, case study of the Matthew Island tsunami of 10 February 2021 and implication in regional hazard assessment
Jean Roger, Bernard Pelletier, Aditya Gusman, William Power, Xiaoming Wang, David Burbidge, and Maxime Duphil
Nat. Hazards Earth Syst. Sci., 23, 393–414, https://doi.org/10.5194/nhess-23-393-2023,https://doi.org/10.5194/nhess-23-393-2023, 2023
Short summary
Detecting anomalous sea-level states in North Sea tide gauge data using an autoassociative neural network
Kathrin Wahle, Emil V. Stanev, and Joanna Staneva
Nat. Hazards Earth Syst. Sci., 23, 415–428, https://doi.org/10.5194/nhess-23-415-2023,https://doi.org/10.5194/nhess-23-415-2023, 2023
Short summary

Cited articles

Abadie, S. D., Morichon, S. D., Grilli, S., and Glockner, S.: Numerical simulation of waves generated by landslides using a multiple-fluid Navier–Stokes model, Coast. Eng., 24, 779–794, 2010. 
Abadie, S. D., Harris, J. C., Grilli, S. T., and Fabre, R.: Numerical modeling of tsunami waves generated by the flank collapse of the Cumbre Vieja Volcano (La Palma, CanaryIslands): Tsunami source and near field effects, J. Geophys. Res., 117, 50–30, 2012. 
Acuna, M. A. and Takayuki, A.: TRITON-G, available at: https://osf.io/fydz8/, 2017. 
Arcas, D. and Titov, V.: Sumatra tsunami: lessons from modeling, Surv. Geophys., 27, 679–705, 2006. 
Babeyko, A.: Fast Tsunami Simulation Tool for Early Warning, available at: https://docs.gempa.de/toast/current/apps/easywave.html (last access: 13 September 2018), 2017. 
Download
Short summary
Tsunamis like those in Indonesia in 2004 and Japan in 2011 have shown like never before the destructive power of this natural disaster. This highlighted the importance of fast and accurate simulations for forecasting. We present a fully GPU-accelerated tsunami model for large domains that delivers results within minutes with high accuracy and efficient resource use. By using just three GPUs, results for the Indian Ocean were obtained in 15 min. This allows for fast evacuation and risk decisions.
Altmetrics
Final-revised paper
Preprint