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Probabilistic Tsunami Hazard Analysis: High Performance Computing for Massive Scale Inundation Simulations Gibbons, Steven Lorito, Stefano Macías-Sánchez, Jorge Lovholt, Finn Selva, Jacopo Volpe, Manuela Sánchez-Linares, Carlos Babeyko, Andrey Brizuela, Beatriz Cirella, Antonella Castro, Manuel Jesús de la Asunción, Marc Lanucara, Piero Glimsdal, Sylfest Lorenzino, Maria Concetta Nazaria, Massimo Pizzimenti, Luca Romano, Fabrizio Scala, Antonio Tonini, Roberto González-Vida, José Manuel Vöge, Malte Maremotos Probabilistic Tsunami Hazard Analysis (PTHA) quantifies the probability of exceeding a specified inundation intensity at a given location within a given time interval. PTHA provides scientific guidance for tsunami risk analysis and risk management, including coastal planning and early warning. Explicit computation of site-specific PTHA, with an adequate discretization of source scenarios combined with high-resolution numerical inundation modelling, has been out of reach with existing models and computing capabilities, with tens to hundreds of thousands of moderately intensive numerical simulations being required for exhaustive uncertainty quantification. In recent years, more efficient GPU-based High-Performance Computing (HPC) facilities, together with efficient GPU-optimized shallow water type models for simulating tsunami inundation, have now made local long-term hazard assessment feasible. A workflow has been developed with three main stages: 1) Site-specific source selection and discretization, 2) Efficient numerical inundation simulation for each scenario using the GPU-based Tsunami-HySEA numerical tsunami propagation and inundation model using a system of nested topo-bathymetric grids, and 3) Hazard aggregation. We apply this site-specific PTHA workflow here to Catania, Sicily, for tsunamigenic earthquake sources in the Mediterranean. We illustrate the workflows of the PTHA as implemented for High-Performance Computing applications, including preliminary simulations carried out on intermediate scale GPU clusters. We show how the local hazard analysis conducted here produces a more fine-grained assessment than is possible with a regional assessment. 2024-09-23T11:53:54Z 2024-09-23T11:53:54Z 2020-12-11 journal article Gibbons SJ, Lorito S, Macías J, Løvholt F, Selva J, Volpe M, Sánchez-Linares C, Babeyko A, Brizuela B, Cirella A, Castro MJ, de la Asunción M, Lanucara P, Glimsdal S, Lorenzino MC, Nazaria M, Pizzimenti L, Romano F, Scala A, Tonini R, Manuel González Vida J and Vöge M (2020) Probabilistic Tsunami Hazard Analysis: High Performance Computing for Massive Scale Inundation Simulations. Front. Earth Sci. 8:591549. doi: 10.3389/feart.2020.591549 https://hdl.handle.net/10630/32905 10.3389/feart.2020.591549 eng http://creativecommons.org/licenses/by-nc-nd/4.0/ open access Attribution-NonCommercial-NoDerivatives 4.0 Internacional Frontiers