A tsunami hazard assessment was conducted for the communities of Sigatoka and Cuvu, located on the island of Viti Levu, Fiji. The study presents an overview of historical seismic and tsunami impact on the Pacific Island nation of Fiji in order to identify source areas of relevance to the study. In addition, the sensitivity of the Coral Coast of Viti Levu to tsunamis coming from different parts of the New Hebrides and Tonga-Kermadec Subduction zones was investigated and used to select worst case tsunami scenarios. Following the methodology developed at the NOAA Center for Tsunami Research (Tang et al, 2006) more than 40 tsunami simulations were conducted on a low-resolution model. Four of the sources simulated were selected as the most hazardous to the area of interest and were subsequently modeled on a high-resolution (10 meter) grid of Sigatoka and Cuvu. To these sources, an ensemble of 20 additional sources in the Tonga-Kermadec Subduction Zone were selected for evaluation. These sources were identified in an Intergovernmental Oceanographic Commission (IOC) report (IOC Working Report No. 289, 2018) by a group of seismic experts on tsunami sources in the region. Finally, one source from a 2022 study conducted by NCTR for the US Department of State to assess tsunami hazard to the city of Suva, Fiji using a probabilistic approach was selected for simulation on the high-resolution model. The non-linear shallow water wave inundation Method Of Splitting Tsunami (MOST) model (Titov and Gonz\'alez, 1997) is one of the tsunami modeling codes in use by the National Tsunami Hazard Mitigation Program (NTHMP, 2011), (NTHMP, 2017) of the US to conduct tsunami inundation studies with the purpose of developing evacuations maps. The MOST code was used in this study to determine tsunami maximum amplitude, arrival and duration times, flow depths, tsunami inundation, current speeds and attenuation.

NOAA Pacific Marine Environmental Laboratory’s (PMEL’s) approach to tsunami research is unique among such laboratories in that tsunami observations and modeling are under one roof, offering the advantages of enhancing the speed and lowering the cost of developments. Here, we chronicle the history of the transfer of deep-ocean observational and flooding modeling technologies within and outside of NOAA and provide a case study for future transfers. PMEL and partners’ efforts in transferring tsunami technology have been very successful, resulting in improved protection of global communities with high tsunami risk while enhancing the new blue economy. The transfer of observational technology within NOAA required years of effort, while the transfer outside of NOAA only required a patent and license agreement. During the transfer process, three additional generations of observational technologies were created. The transfer of tsunami flooding modeling technology required a validation process for transfer into NOAA operations and an international training program to allow access to the technology by other countries. During this model development, a web-based product was created to simplify the use of and access to these models for both real-time and hazard assessment applications. We present lessons learned from these transfers, including the need for support as long as the technology is in use. The tsunami transfer process created a wealth of economic expansion while protecting coastal citizens from future tsunamis.

A modeling study has been conducted to simulate the June 13, 2013 U.S. East Coast meteotsunami event as a test of the model forecast concept. A numerical simulation based on the MOST (Method of Splitting Tsunami) model was employed for the meteotsunami propagation forecast, while the weather radar reflection imagery was used to simulate real-time input data for the atmospheric pressure-induced tsunami generation. The model tsunami was generated by a moving pressure field during 2.87 h of forcing, and the resultant tsunami was then simulated for additional 5.68 h of propagation without any forcing for a total of 8.55 h of meteotsunami evolution from generation to coastal impact. Simulated time series were compared with the measurements from sea-level coastal gages and the Deep-ocean Assessment and Reporting for Tsunami (DART) data. The model is able to reproduce in general the recorded sea-level changes in the deep ocean and at the coast in terms of arrival times and amplitudes. The model was able to predict coastal tsunami impacts that occurred from one to two hours after the model data assimilation phase ended. Therefore, this approach shows promise for developing meteotsunami model forecast capability based on measurements and data assimilation in real time, at least for meteotsunamis generated by fast-moving weather systems visible on radar reflection imagery. All the data used in this study are already available in real time, the MOST model is already implemented as a seismically generated tsunami forecast model at the Tsunami Warning Centers (TWCs), which makes transition of potential meteotsunami forecast capability to warning operations straightforward.

The 2004 Sumatra tsunami was an unprecedented global disaster measured throughout the world oceans. The present study focused on a region of the southeastern Pacific Ocean where the westward circumferentially propagating tsunami branch converged with the eastward branch, based on data from fortuitously placed Chilean DART 32401 and tide gauges along the coast of South America. By comparison of the tsunami and background spectra, we suppressed the influence of topography and reconstructed coastal spectral ratios that were in close agreement with a ratio at DART 32401 and spectral ratios in other oceans. Findings indicate that even remote tsunami records carry spectral source signatures (birth-marks). The 2004 tsunami waves were found to occupy the broad frequency band of 0.25-10 cph with the prominent ratio peak at period of 40 min related to the southern fast-slip source domain. This rupture hot-spot of approximate to 350 km was responsible for the global impact of the 2004 tsunami. Data from DART 32401 provided validation of model results: the simulated maximum tsunami wave height of 2.25 cm was a conservative approximation to the measured height of 2.05 cm; the computed tsunami travel time of 25 h 35 min to DART 32401, although 20 min earlier than the actual travel time, provided a favorable result in comparison with 24 h 25 min estimated from classical kinematic theory. The numerical simulations consistently reproduced the wave height changes observed along the coast of South America, including local amplification of tsunami waves at the northern stations of Arica (72 cm) and Callao (67 cm).

The magnitude 8.3 earthquake in central Chile on 16 September 2015 and the resulting tsunami severely affected the region, with 15 deaths (Onemi in Monitoreo por sismo de mayor intensidad. (In Spanish) [Available at: http://www.onemi.cl/alerta/se-declara-alerta-roja-por-sismo-de-mayor-intensidad-y-alarma-de-tsunami/], 2015), over one million evacuated, and flooding in nearby coastal cities. We present our real-time assessment of the 2015 Chile tsunami using the Short-term Inundation Forecasting for Tsunamis system, and post-event analyses with local community models in Chile. We evaluate three real-time tsunami sources, which were inverted at the time that the first quarter-, half-, and full-wave passed the first tsunameter (DART 32402, located approximately 580 km north–northwest of the epicenter), respectively. Measurement comparisons from 26 deep-ocean tsunameters and 38 coastal tide stations show that good model accuracies are achieved for all three sources, particularly for the local sites that recorded the most destructive waves. The study highlights the forecast speed, time and accuracy dependence, and their implications for the local forecast capability. Our analyses suggest that the tsunami's main origination area is about 100–200 km long and 100 km wide, to the north of the earthquake epicenter along the trench and the total estimated tsunami wave energy is 7.9 × 1013 J (with 13 % uncertainty). The study provides important guidelines for the earliest reliable estimate of tsunami energy and local forecasts. They can be obtained with the first quarter-wave of tsunameter recording. These results are also confirmed by a forecast analysis of the 2011 Japan tsunami. Furthermore, we find that the first half-wave tsunameter data are sufficient to accurately forecast the 2015 Chile tsunami, due to the specific orientation between the nearest tsunameter and the source. The study also suggests expanding the operational use of the local community models in real time, and demonstrates the applicability of the model results for “all-clear” evaluations, search and rescue operations, and near-real-time mitigation planning in both near and far fields.

Model forecast applications use various models of tsunami sources inferred from different measurement data. Even the same type of observation data can produce substantially different tsunami source models during a real-time forecast when more data are obtained during the real-time analysis. Improved tsunami observations enable investigation of the influence of such model source variability on the final forecast using different source data sets of several events. The 2010 Maule, Chile and 2011 Tohoku, Japan tsunamis were two recent events that provide ample observations throughout the Pacific and were, thus, used here to study the sensitivity of different model inputs for forecasting. The sources for these events were derived using the following three different methods: (1) real time or post event inversion of tsunameter water level data; (2) prediction of sea floor deformations via analysis of seismic wave forms and application of a finite fault model; and (3) prediction of sea floor deformation using real-time GPS data. For the March 11, 2011 Tohoku tsunami, two examples of each method are used, while for the February 27, 2010 Maule event, only one tsunameter inversion and one finite fault model method were used due to a much more limited data set. Observed data from the Deep-ocean Assessment and Reporting for Tsunamis (DART) network, Japan GPS buoys, and select tide gauges across the Pacific were compared with forecasts to assess the sensitivity of these three methods using root-mean-square error analysis. We divided the analysis by the type of data and the distance from the source. This sensitivity analysis showed that increasing the resolution of a tsunami source model does not necessarily improve tsunami forecast quality, even in the near-field. Instead, the findings suggest that when forecasting coastal impact, defining the overall energy characteristic of a tsunami source may be more important than refining small source details. Source models based on direct tsunami observations are better at reproducing a tsunami signal: this finding is not very surprising but has implications for tsunami forecasting and warning operations.

This work examines the extent to which tsunami forecasts from different numerical forecast systems might be expected to differ under real-time conditions. This is done through comparing tsunami amplitudes from a number of existing tsunami scenario databases for eight different hypothetical tsunami events within the Indian Ocean. Forecasts of maximum tsunami amplitude are examined at 10 output points distributed throughout the Indian Ocean at a range of depths. The results show that there is considerable variability in the forecasts and on average, the standard deviation of the maximum amplitudes is approximately 62% of the mean value. It is also shown that a significant portion of this diversity can be attributed to the different lengths of the scenario time series. These results have implications for the interoperability of Regional Tsunami Service Providers in the Indian Ocean.

Tsunamis are long waves that evolve substantially, through spatial and temporal spreading from their source region. Here, we introduce a new analytical solution to study the propagation of a finite strip source over constant depth using linear shallow-water wave theory. This solution is not only exact, but also general and allows the use of realistic initial waveforms such as N-waves. We show the existence of focusing points for N-wave-type initial displacements, i.e. points where unexpectedly large wave heights may be observed. We explain the effect of focusing from a strip source analytically, and explore it numerically. We observe focusing points using linear non-dispersive and linear dispersive theories, analytically; and nonlinear non-dispersive and weakly nonlinear weakly dispersive theories, numerically. We discuss geophysical implications of our solutions using the 17 July 1998 Papua New Guinea and the 17 July 2006 Java tsunamis as examples. Our results may also help to explain high run-up values observed during the 11 March 2011 Japan tsunami, which are otherwise not consistent with existing scaling relationships. We conclude that N-waves generated by tectonic displacements feature focusing points, which may significantly amplify run-up beyond what is often assumed from widely used scaling relationships.

We have developed a method to compute the total energy transmitted by tsunami waves, to the case where the earthquake source is unknown, by using deep‐ocean pressure measurements and numerical models (tsunami source functions). Based on the first wave recorded at the two closest tsunameters (Deep‐Ocean Assessment and Reporting of Tsunamis (DART)), our analysis suggests that the March 11, 2011 Tohoku‐Oki tsunami generated off Japan originated from a 300–400 km long and 100 km wide area, and the total propagated energy is 3 × 1015J (with 6% uncertainty). Measurements from 30 tsunameters and 32 coastal tide stations show excellent agreement with the forecasts obtained in real time. Our study indicates that the propagated energy and the source location are the most important source characteristics for predicting tsunami impacts. Interactions of tsunami waves with seafloor topography delay and redirect the energy flux, posing hazards from delayed and amplified waves with long duration. Seafloor topography also gives its spectral imprint to tsunami waves. Travel time forecast errors are path‐specific and correlated to the major wave scatterers in the Pacific. Numerical dissipation in the propagation modeling highlights the need of high‐resolution inundation models for accurate coastal predictions. On the other hand, it also can be used to account for physical dissipation to achieve efficiency. Our results provide guidelines for the earliest reliable tsunami forecast, warnings of long duration tsunami waves signals and enhancement of the experimental tsunami forecast system. We apply the method to quantify the energy of 15 past tsunamis, independently from earthquake magnitudes. The small tsunami to seismic radiation energy ratios, and their variability (0.01–0.8%), reinforce the importance of using deep‐ocean tsunami data, the direct measures of tsunamis, for estimates of tsunami energy and accurate forecasting.