Abstract For New Zealand, a country straddling the Pacific ‘Ring of Fire’, effective mitigation of the risks posed by tsunamis is an urgent priority. Mitigation measures include evacuation mapping, land-use planning and engineering of tsunami resilient buildings and infrastructure; but for these to be effective, a quantitative estimate of the tsunami hazard is needed. For this purpose we present the New Zealand Probabilistic Tsunami Hazard Model (NZPTHM). The model uses a Monte Carlo method for sampling from the geophysical parameters that constrain the magnitude–frequency distributions of the earthquake sources that can cause tsunamis affecting New Zealand. The sampled parameters are used to construct synthetic catalogues of the source events and the subsequent tsunami heights. Processing of these synthetic catalogues produces hazard curves, describing maximum tsunami height as a function of return period, which include ‘error bars’ (confidence intervals) as determined by the Monte Carlo model. Most practical mitigation measures require inundation modelling, and for this purpose we propose using de-aggregation, a process by which a small set of scenarios can be extracted from the NZPTHM for the purpose of detailed inundation modelling.

Abstract Large tsunamis occur infrequently but have the capacity to cause enormous numbers of casualties, damage to the built environment and critical infrastructure, and economic losses. A sound understanding of tsunami hazard is required to underpin management of these risks, and while tsunami hazard assessments are typically conducted at regional or local scales, globally consistent assessments are required to support international disaster risk reduction efforts, and can serve as a reference for local and regional studies. This study presents a global-scale probabilistic tsunami hazard assessment (PTHA), extending previous global-scale assessments based largely on scenario analysis. Only earthquake sources are considered, as they represent about 80% of the recorded damaging tsunami events. Globally extensive estimates of tsunami run-up height are derived at various exceedance rates, and the associated uncertainties are quantified. Epistemic uncertainties in the exceedance rates of large earthquakes often lead to large uncertainties in tsunami run-up. Deviations between modelled tsunami run-up and event observations are quantified, and found to be larger than suggested in previous studies. Accounting for these deviations in PTHA is important, as it leads to a pronounced increase in predicted tsunami run-up for a given exceedance rate.