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.
This article chronicles the 50-year history of tsunami research and development at the NOAA Pacific Marine Environmental Laboratory (PMEL), beginning with the merger in 1973 of the Joint Tsunami ...Research Effort and PMEL. It traces the development of instrumentation and modeling that brought a better understanding of tsunamis and improved warning systems. The advantage of having observational engineering and flooding modeling under one roof are highlighted. Deepocean Assessment and Reporting of Tsunami (DART) research and development led to technology transfer to NOAA’s National Data Buoy Center (NDBC) that now operates and maintains 39 buoys and serves as real-time data distributor for other nations. This technology was also patented and licensed by PMEL to meet the needs of the international community. DART licensee Science Applications International Corporation (SAIC) has manufactured over 60 buoys for eight different countries. DART data are essential for accurate tsunami warnings, so the global society benefits by receiving lifesaving information before the arrival of a tsunami.
PMEL’s tsunami flooding modeling research led to technology transfer to NOAA’s tsunami warning centers, the National Tsunami Hazard Mitigation Program, and international tsunami preparedness communities. Short-term flooding modeling research was initiated at PMEL to improve NOAA tsunami warning operations to better serve US coastal communities. The same validated modeling technology was then applied to produce hazard maps for coastal communities in the United States and internationally through the United Nations’ Intergovernmental Oceanographic Commission (IOC). Tsunami hazard maps are an essential first step in preparing a community for the next tsunami. Using these maps and other preparedness criteria, a community can become “Tsunami Ready” for the next event. Tsunami Ready has been adopted by the IOC as the global standard for preparedness of at-risk communities with total populations exceeding 890 million people.
Within 4 months of 2018, two fatal tsunamis struck islands of Indonesia with ferocity that astonished local population, tsunami warning systems and scientists. For both of these events, the September ...28 Palu Bay tsunami in Sulawesi and the 22 December Anak Krakatau tsunami in Sunda Strait, the initial tsunami source data was either non-suggestive or simply non-existent to imply such a devastating wave impact. International teams of scientists, members of the International Tsunami Survey Team, descended to Indonesia to help local scientists collecting all possible data from these two events, investigating the origins of these tsunamis to explain the unexpected tsunami strength. The analysis of the observation data presented in this collection of papers mostly explains the unexpectedly devastating impact from these two unusual tsunami events. The lessons learned from the response to these two events coupled with the new scientific understanding of tsunami genesis will provide improved guidance for more effective tsunami warning operations for Indonesia and the coastlines around the World.
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.
During the devastating 11 March 2011 Japanese tsunami, data from two tsunami detectors were used to determine the tsunami source within 1.5 h of earthquake origin time. For the first time, multiple ...near-field tsunami measurements of the 2011 Japanese tsunami were used to demonstrate the accuracy of the National Oceanic and Atmospheric Administration (NOAA) real-time flooding forecast system in the far field. To test the accuracy of the same forecast system in the near field, a total of 11 numerical models with grids telescoped to 2 arcsec (~60 m) were developed to hindcast the propagation and coastal inundation of the 2011 Japanese tsunami along the entire east coastline of Japan. Using the NOAA tsunami source computed in near real-time, the model results of tsunami propagation are validated with tsunami time series measured at different water depths offshore and near shore along Japan’s coastline. The computed tsunami runup height and spatial distribution are highly consistent with post-tsunami survey data collected along the Japanese coastline. The computed inundation penetration also agrees well with survey data, giving a modeling accuracy of 85.5 % for the inundation areas along 800 km of coastline between Ibaraki Prefecture (north of Kashima) and Aomori Prefecture (south of Rokkasho). The inundation model results highlighted the variability of tsunami impact in response to different offshore bathymetry and flooded terrain. Comparison of tsunami sources inferred from different indirect methods shows the crucial importance of deep-ocean tsunami measurements for real-time tsunami forecasts. The agreement between model results and observations along Japan’s coastline demonstrate the ability and potential of NOAA’s methodology for real-time near-field tsunami flooding forecasts. An accurate tsunami flooding forecast within 30 min may now be possible using the NOAA forecast methodology with carefully placed tsunameters and large-scale high-resolution inundation models with powerful computing capabilities.
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 × 10
13
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.
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.
Key Points
Deep‐ocean tsunami data provide a robust and direct measure of tsunami energy
Propagation energy is the key for accurate and effective tsunami forecasts
Energy for the past 15 tsunamis were quantified independently from seismic data
In this study, we investigate the dispersive effects in the 2009 Samoa tsunami through numerical simulations. The wave propagation is first simulated with a weakly nonlinear and dispersive Boussinesq ...model and a non‐dispersive shallow‐water‐equations model. Comparison of the numerical results between these models indicates that tsunami propagation is significantly affected by the frequency dispersion east of Tonga Trench. Neglecting dispersive effects results in larger wave heights and speeds. The strong frequency dispersion is primarily attributed to the dramatic variation of water surface elevations generated by the earthquake doublet, and enhanced by the uneven bathymetry in Tonga Trench. Tsunami propagation is also simulated with MOST (“Method of Splitting Tsunamis”), which is based on the shallow water equations but uses numerical dispersion to mimic physical frequency dispersion at operational resolutions. A good agreement is observed between MOST and the Boussinesq model, as well as the field measurements in the leading wave. In the shorter trailing waves, agreement becomes poorer due to the mismatch between numerical and physical dispersions.
Key Points
The earthquake‐doublet generated a tsunami with strong dispersive effects
Neglecting dispersion can result in over‐predicated wave heights and speeds
MOST may be applied to modeling weakly dispersive tsunamis at basin scales
Correctly characterizing tsunami source generation is the most critical component of modern tsunami forecasting. Although difficult to quantify directly, a tsunami source can be modeled via different ...methods using a variety of measurements from deep-ocean tsunameters, seismometers, GPS, and other advanced instruments, some of which in or near real time. Here we assess the performance of different source models for the destructive 11 March 2011 Japan tsunami using model–data comparison for the generation, propagation, and inundation in the near field of Japan. This comparative study of tsunami source models addresses the advantages and limitations of different real-time measurements with potential use in early tsunami warning in the near and far field. The study highlights the critical role of deep-ocean tsunami measurements and rapid validation of the approximate tsunami source for high-quality forecasting. We show that these tsunami measurements are compatible with other real-time geodetic data, and may provide more insightful understanding of tsunami generation from earthquakes, as well as from nonseismic processes such as submarine landslide failures.
The Global Reach of the 26 December 2004 Sumatra Tsunami Titov, Vasily; Rabinovich, Alexander B.; Mofjeld, Harold O. ...
Science (American Association for the Advancement of Science),
09/2005, Letnik:
309, Številka:
5743
Journal Article
Recenzirano
Odprti dostop
Numerical model simulations, combined with tide-gauge and satellite altimetry data, reveal that wave amplitudes, directionality, and global propagation patterns of the 26 December 2004 Sumatra ...tsunami were primarily determined by the orientation and intensity of the offshore seismic line source and subsequently by the trapping effect of mid-ocean ridge topographic waveguides.
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