Method Of Splitting Tsunami Research Articles

Meteotsunami model forecast: can coastal hazard be quantified in real time?

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.

Evaluations of OpenCL-written tsunami simulation on FPGA and comparison with GPU implementation

When a tsunami occurred on a sea area, prediction of its arrival time is critical for evacuating people from the coastal area. There are many problems related to tsunami to be solved for reducing negative effects of this serious disaster. Numerical modeling of tsunami wave propagation is a computationally intensive problem which needs to accelerate its calculations by parallel processing. The method of splitting tsunami (MOST) is one of the well-known numerical solvers for tsunami modeling. We have developed a tsunami propagation code based on MOST algorithm and implemented different parallel optimizations for GPU and FPGA. In the latest study, we have the best performance of OpenCL kernel which is implemented tsunami simulation on AMD Radeon 280X GPU. This paper targets on design and evaluation on FPGA using OpenCL. The performance on FPGA design generated automatically by Altera offline compiler follows the results of GPU by several kernel modifications.

TSUNAMI RISK ASSESSMENT MODELLING IN CHABAHAR PORT, IRAN

Abstract. The well-known historical tsunami in the Makran Subduction Zone (MSZ) region was generated by the earthquake of November 28, 1945 in Makran Coast in the North of Oman Sea. This destructive tsunami killed over 4,000 people in Southern Pakistan and India, caused great loss of life and devastation along the coasts of Western India, Iran and Oman. According to the report of "Remembering the 1945 Makran Tsunami", compiled by the Intergovernmental Oceanographic Commission (UNESCO/IOC), the maximum inundation of Chabahar port was 367 m toward the dry land, which had a height of 3.6 meters from the sea level. In addition, the maximum amount of inundation at Pasni (Pakistan) reached to 3 km from the coastline. For the two beaches of Gujarat (India) and Oman the maximum run-up height was 3 m from the sea level. In this paper, we first use Makran 1945 seismic parameters to simulate the tsunami in generation, propagation and inundation phases. The effect of tsunami on Chabahar port is simulated using the ComMIT model which is based on the Method of Splitting Tsunami (MOST). In this process the results are compared with the documented eyewitnesses and some reports from researchers for calibration and validation of the result. Next we have used the model to perform risk assessment for Chabahar port in the south of Iran with the worst case scenario of the tsunami. The simulated results showed that the tsunami waves will reach Chabahar coastline 11 minutes after generation and 9 minutes later, over 9.4 Km2 of the dry land will be flooded with maximum wave amplitude reaching up to 30 meters.

QUANTIFYING NUMERICAL MODEL ACCURACY AND VARIABILITY

On March 11, 2011 the Tohoku tsunami event caused the death of thousands of people and generated billions of dollars in damages. Following this and previous tsunami events, there has been an effort to improve tsunami risk mitigation for coastal communities. Currently, numerical models are being used in a state-of-the-art methodology to estimate tsunami risk from near and far field sources. Model predictions are essential for the development of Tsunami Hazard Assessments (THA). By better understanding model bias and uncertainties and if possible minimizing them, a more accurate and reliable THA will result. In this study we compare runup height, inundation lines and flow velocity field measurements between GeoClaw and the Method Of Splitting Tsunami (MOST) predictions in the Sendai plain. Runup elevation and average inundation distance was in general over predicted by the models. However, both models agree relatively well with each other when predicting maximum sea surface elevation and maximum flow velocities. Model predictions show that the flow velocity increases as the tsunami wave front reaches the shoreline and makes its way inland for a couple of kilometers, contrary to what it is generally assumed. The tsunami models used in this study show much more variability when predicting flow velocity than predicting runup elevations and inundation lines. The results provided in this study will help understand the uncertainties in model predictions and locate possible sources of errors within a model.

Real-Time Detection of Tsunami Ionospheric Disturbances with a Stand-Alone GNSS Receiver: A Preliminary Feasibility Demonstration

It is well known that tsunamis can produce gravity waves that propagate up to the ionosphere generating disturbed electron densities in the E and F regions. These ionospheric disturbances can be studied in detail using ionospheric total electron content (TEC) measurements collected by continuously operating ground-based receivers from the Global Navigation Satellite Systems (GNSS). Here, we present results using a new approach, named VARION (Variometric Approach for Real-Time Ionosphere Observation), and estimate slant TEC (sTEC) variations in a real-time scenario. Using the VARION algorithm we compute TEC variations at 56 GPS receivers in Hawaii as induced by the 2012 Haida Gwaii tsunami event. We observe TEC perturbations with amplitudes of up to 0.25 TEC units and traveling ionospheric perturbations (TIDs) moving away from the earthquake epicenter at an approximate speed of 316 m/s. We perform a wavelet analysis to analyze localized variations of power in the TEC time series and we find perturbation periods consistent with a tsunami typical deep ocean period. Finally, we present comparisons with the real-time tsunami MOST (Method of Splitting Tsunami) model produced by the NOAA Center for Tsunami Research and we observe variations in TEC that correlate in time and space with the tsunami waves.

Hypothetical Tsunami Scenarios and Evacuation Intention: A Case Study of Orange County, California

Historically, California has had 14 tsunamis since 1812 where the heights of the waves were higher than three feet. One of California’s major tsunamis followed the 1964 Alaskan earthquake and caused 12 deaths, with damages totaling to at least 17 million dollars. According to Jose Borrero and Costas Synolakis in their report, “Tsunami Inundation Mapping, Field Survey Report and Final Recommendations for Orange County”, the worst case Tsunami scenario in Orange County, California, is a wave of approximately 10 meters or 32.81 feet (Tsunami Annex, 2009). Having evidence of historical tsunami events, even if not major ones, in addition to the probabilities of tsunami occurrences in the future requires the attention of both responsible administrative officials and the foundation of sound research directed toward planning for such events. The goal of this study is to measure how the surveyed population would respond in different, hypothetical tsunami scenarios should Orange County Officials advise the population to evacuate. The methodology consists of a survey of 235 people who live along the coastal area of Orange County, California. Method of Splitting Tsunami (MOST) model maps and GIS were used to delineate the evacuation and shadow evacuation zones in order to locate the spatial distribution of the population within these two zones. The results of this research indicated that the evacuation participation rate increases as the heights of the tsunami waves increase. The average socioeconomic characteristics of the sampled population vary from the sampled population when compared with the 2010 US Census data. This research may be useful for emergency managers, policy and decision makers.

FPGA-based tsunami simulation: Performance comparison with GPUs, and roofline model for scalability analysis

MOST (Method Of Splitting Tsunami) is widely used to solve shallow water equations (SWEs) for simulation of tsunami. This paper presents high-performance and power-efficient computation of MOST for practical tsunami simulation with FPGA. The custom hardware for simulation is based on a stream computing architecture for deeply pipelining to increase performance with a limited bandwidth. We design a stream processing element (SPE) of computing kernels combined with stencil buffers. We also introduce an SPE array architecture with spatial and temporal parallelism to further exploit available hardware resources by implementing multiple SPEs with parallel internal pipelines. Our prototype implementation with Arria 10 FPGA demonstrates that the FPGA-based design performs numerically stable tsunami simulation with real ocean-depth data in single precision by introducing non-dimensionalization. We explore the design space of SPE arrays, and find that the design of six cascaded SPEs with a single pipeline achieves the sustained performance of 383 GFlops and the performance per power of 8.41 GFlops/W with a stream bandwidth of only 7.2 GB/s. These numbers are 8.6 and 17.2 times higher than those of NVidia Tesla K20c GPU, and 1.7 and 7.1 times higher than those of AMD Radeon R9 280X GPU, respectively, for the same tsunami simulation in single precision. Moreover, we proposed a roofline model for stream computing with the SPE array in order to investigate factors of performance degradation and possible performance improvement for given FPGAs. With the model, we estimate that an upcoming Stratix 10 GX2800 FPGA can achieve the sustained performance of 8.7 TFlops at most with our SPE array architecture for tsunami simulation.

Development of MOST for Real-Time Tsunami Forecasting

AbstractThe development, testing, and implementation of a real-time tsunami forecast model, the method of splitting tsunami (MOST), is described. MOST is now used as an operational forecast model for the National Oceanic and Atmospheric Administration’s Tsunami Warning System, and as a tsunami hazard assessment tool in the United States and in many countries around the world. Every step in the development of MOST marked new scientific challenges, improvements of technological and computational capabilities, and new demands of the engineering and hazard mitigation communities for applied and benchmark modeling tools for tsunami hazard assessment.

Spatial Statistics of Tsunami Overland Flow Properties

AbstractNumerical models are a key component of methodologies used to estimate tsunami risk, and model predictions are essential for the development of tsunami hazard assessments (THAs). By better understanding model bias and variability and, if possible, minimizing them, more reliable THAs will result. In this study, the authors compare run-up height, inundation lines, and flow-velocity field measurements between an open-source tsunami model and the method of splitting tsunami (MOST) model predictions in the Sendai Plain in Japan. Run-up elevation and average inundation distance are, in general, overpredicted by the models. However, both models agree relatively well with each other when predicting maximum sea surface elevations and maximum flow velocities. Furthermore, to explore the variability in numerical models, MOST is used to compare predictions from six different grid resolutions (90, 60, 30, 20, 15, and 10 m). Results of this work show that predictions of statistically stable products (run-up, in...

Stream Computation of Shallow Water Equation Solver for FPGA-based 1D Tsunami Simulation

MOST (Method Of Splitting Tsunami) is widely used to solve shallow water equations (SWEs) for forecasting tsunami generated by an earthquake. Toward development of a power-efficient and high-performance computing system for 2D tsunami simulation, we conduct feasibility study on stream computation of 1D SWE solver with FPGA.We analyze an original code and design a stream algorithm with techniques of kernel fusion, shift buffering for streamed stencil-data access, and cascading processing elements for a longer pipeline. We implement a deep pipeline with at most 744 stages of 4 SPEs on 28 nm Stratix V FPGA, which achieves 82.4 GFlop/s at 200 MHz.

Far-Field Tsunami Hazard in New Zealand Ports

We present the results of a numerical modeling study investigating the effects of far-field tsunamis in New Zealand ports. Four sites (Marsden Point, Tauranga, Harbor, Port Taranaki and Lyttelton Harbor) were selected based on a combination of factors such as economic importance and the availability of historical and/or instrumental data. Numerical models were created using the ComMIT tsunami modeling tool and the Method Of Splitting Tsunami (MOST) hydrodynamic model. Comparison of model results to measured data from recent historical events showed that, for particular sites and events, the model correlated well with the timing and amplitude of the observed tsunami, and, in most cases, there was generally good agreement between the and modeled tsunami heights and current speeds. A sensitivity analysis for tsunami heights and current speeds was conducted using a suite of large (M W 9) tsunamigenic earthquake sources situated at regular 15° intervals in azimuth along the Pacific Rim while another set of scenarios focused on regional tsunami sources in the Southwest Pacific. Model results were analyzed for tsunami heights and current speeds as a function of the source region. In terms of currents, the analysis identified where speeds were greatest and which source was responsible. Results suggested that tsunamis originating from Central America produced the strongest response in New Zealand. The modeling was also used to determine the timing and duration of potentially dangerous current speeds as well as minimum ‘safe depths’ for vessel evacuation offshore. This study was motivated by the desire to reduce damage and operational losses via improved forecasting of far-field tsunamis at New Zealand ports. It is important that forecasts are accurate since tsunami damage to ships and facilities is expensive and can be mitigated given timely warnings and because preventable false alarms are also costly in terms of lost productivity. The modeling presented here will underpin efforts to produce port-specific guidance and information in the event of future Pacific tsunamis.

The Vulnerability of Crescent City, California, to Tsunamis Generated by Earthquakes in the Kuril Islands Region of the Northwestern Pacific

Crescent City, located in Del Norte County on the California coast about 460 k north of San Francisco (Figure 1), has suffered more impacts from historic tsunamis than any other community on the west coast of the United States (Dengler and Magoon 2006). Thirty-one tsunamis have been observed at this small coastal city (population 7,542) since a tide gauge was established in 1933, including 11 events with maximum peak-to-trough wave range exceeding 1 meter and four that caused damage (National Geophysical Data Center 2008; http://www.ngdc.noaa.gov/hazard/tsu_db.shtml). The most recent damaging tsunami, and the first tsunami to cause significant property damage in the United States since 1964, occurred on 15 November 2006. It was caused by an Mw 8.3 earthquake on the central Kuril trench and produced strong currents in Crescent Harbor that damaged docks in the small-boat basin. Five tsunamis generated by earthquakes in the Kuril Islands have been recorded at Crescent City since the tide gauge was installed, but only the 2006 event caused damage. The earthquakes were similar in magnitude (7.9 to 8.4) and varied slightly in location relative to Crescent City. This study examines what happened in the 2006 tsunami at Crescent City and why this tsunami was more damaging than other recent events. We use the Method of Splitting Tsunami (MOST) model (Titov and Gonzales 1997; Titov and Synolakis 1998) to simulate three recent tsunamis triggered by similar-sized earthquakes on the Kuril trench and examine which segments of the Kuril-Japan subduction zones have the greatest potential to impact Crescent City. The Kuril Islands trench in the northwestern Pacific marks the convergent plate boundary between the Pacific and North American plates (Figure 2). The Pacific plate is subducting underneath the Kuril Islands arc in a WNW direction of 81 mm/yr; subduction occurs more rapidly only along …

Andaman Seacoast of Thailand Field Survey after the December 2004 Indian Ocean Tsunami

The post-tsunami runups on the damaged Andaman Sea coastline of Thailand from the tsunami of 26 December 2004 were surveyed by Thai and Korean teams for 99 transects from 23 January to 7 February 2005. The highest runup in Thailand was 15.68 m at Cape Coral, in Phang-nga province, and the longest inundation distance was 3 km at Bang Nieng, in Phang-nga province. The causes of the variation in runup were analyzed by using the method of splitting tsunami (MOST) model, tide gauges, satellite imagery, and field data with topographic charts. The distribution of runups reflects the effects of bathymetry, coastal topography, coastline configuration and slope, the pattern and density of land use, and the biological and geomorphological characteristics of offshore and near-shore areas.