scholarly journals Numerical simulation and first-order hazard analysis of large co-seismic tsunamis generated in the Puerto Rico trench: near-field impact on the North shore of Puerto Rico and far-field impact on the US East Coast

2010 ◽  
Vol 10 (10) ◽  
pp. 2109-2125 ◽  
Author(s):  
S. T. Grilli ◽  
S. Dubosq ◽  
N. Pophet ◽  
Y. Pérignon ◽  
J. T. Kirby ◽  
...  
Keyword(s):  
Puerto Rico ◽  
East Coast ◽  
Hazard Analysis ◽  
Near Field ◽  
Far Field ◽  
Caribbean Islands ◽  
North Shore ◽  
The Us ◽  
Nested Grids ◽  
Us East Coast

Abstract. We perform numerical simulations of the coastal impact of large co-seismic tsunamis, initiated in the Puerto Rican trench, both in far-field areas along the upper US East coast (and other Caribbean islands), and in more detail in the near-field, along the Puerto Rico North Shore (PRNS). We first model a magnitude 9.1 extreme co-seismic source and then a smaller 8.7 magnitude source, which approximately correspond to 600 and 200 year return periods, respectively. In both cases, tsunami generation and propagation (both near- and far-field) are first performed in a coarse 2′ basin scale grid, with ETOPO2 bathymetry, using a fully nonlinear and dispersive long wave tsunami model (FUNWAVE). Coastal runup and inundation are then simulated for two selected areas, using finer coastal nested grids. Thus, a 15″ (450 m) grid is used to calculate detailed far-field impact along the US East Coast, from New Jersey to Maine, and a 3″ (90 m) grid (for the finest resolution), encompassing the entire PRNS, is used to compute detailed near-field impact along the PRNS (runup and inundation). To perform coastal simulations in nested grids, accurate bathymetry/topography databases are constructed by combining ETOPO2 2′ data (in deep water) and USGS' or NOAA's 15″ or 3″ (in shallow water) data. In the far-field, runup caused by the extreme 9.1 source would be severe (over 10 m) for some nearby Caribbean islands, but would only reach up to 3 m along the selected section of the East coast. A sensitivity analysis to the bathymetric resolution (for a constant 3″ model grid) of runup along the PRNS, confirms the convergence of runup results for a topographic resolution 24″ or better, and thus stresses the importance of using sufficiently resolved bathymetric data, in order to accurately predict extreme runup values, particularly when bathymetric focusing is significant. Runup (10–22 m) and inundation are found to be very large at most locations for the extreme 9.1 source. Both simulated spatial inundation snapshots and time series indicate, the inundation would be particularly severe near and around the low-lying city of San Juan. For the 8.7 source, runup along the PRNS would be much less severe (3–6 m), but still significant, while inundation would only be significant near and around San Juan. This first-order tsunami hazard analysis stresses the importance of conducting more detailed and comprehensive studies, particularly of tsunami hazard along the PRNS, for a more complete and realistic selection of sources; such work is ongoing as part of a US funded (NTHMP) tsunami inundation mapping effort in Puerto Rico.

scholarly journals Tsunami Coastal Hazard Along the Us East Coast From Coseismic Sources in the açores Convergence Zone and the Caribbean Arc Areas

2021 ◽  
Author(s):  
Stephan Toni Grilli ◽  
Maryam Mohammadpour ◽  
Lauren Schambach ◽  
Annette Grilli
Keyword(s):  
Puerto Rico ◽  
Return Period ◽  
East Coast ◽  
Tsunami Hazard ◽  
Convergence Zone ◽  
Coastal Hazard ◽  
The Past ◽  
The Us ◽  
Nested Grids ◽  
Us East Coast

Abstract We model the coastal hazard caused by tsunamis along the US East Coast (USEC) for far-field coseismic sources originated in the A\c{c}ores Convergence Zone (ACZ), and the Puerto Rico Trench (PRT)/Caribbean Arc area. In earlier work, similar modeling was performed for probable maximum tsunamis (PMTs) resulting from coseismic, submarine mass failure and volcanic collapse sources in the Atlantic Ocean basin, based on which tsunami inundation maps were developed in high hazard areas of the USEC. Here, in preparation for a future Probabilistic Tsunami Hazard Analysis (PTHA), we model a collection of 18 coseismic sources with magnitude ranging from M8 to M9 and return periods estimated in the 100-2,000 year range. Most sources are hypothetical, based on the seismo-tectonic data known for the considered areas. However, the largest sources from the ACZ, which includes the region of the Madeira Tore Rise, are parameterized as repeats of the 1755 M8.6-9 (Lisbon) earthquake and tsunami using information from many studies published on this event, which is believed to have occurred east of the MTR. Many other large events have been documented to have occurred in this area in the past 2,000 years. There have also been many large historical coseismic tsunamis in and near the Puerto Rico Trench (PRT) area, triggered by earthquakes with the largest in the past 225 years having an estimated M8.1 magnitude. In this area, coseismic sources are parameterized based on information from a 2019 USGS Powell Center expert, attended by the first author, and a collection of SIFT subfaults for the area (Gica et al., 2008). For each source, regional tsunami hazard assessment is performed along the USEC at a coarse 450 m resolution by simulating tsunami propagation to the USEC with FUNWAVE-TVD (a nonlinear and dispersive (2D) Boussinesq model), in nested grids. Tsunami coastal hazard is represented by four metrics, computed along the 5 m isobath, which quantify inundation, navigation, structural, and evacuation hazards: (1) maximum surface elevation; (2) maximum current velocity; (3) maximum momentum force; and (4) tsunami arrival time. Overall, the first three factors are larger, the larger the source magnitude, and their alongshore variation shows similar patterns of higher and lower values, due to bathymetric control from the wide USEC shelf, causing similar wave refraction patterns of focusing/defocusing for each tsunami. The fourth factor differs mostly between sources from each area (ACZ and PRT), but less so among sources from the same area; its inverse is used as a measure of increased hazard associated with short warning/evacuation times. Finally, a new tsunami intensity index (TII) is computed, that attaches a score to each metric within 5 hazard intensity classes selected for each factor, reflecting low, medium low, medium, high and highest hazard, and is computed as a weighted average of these scores (weights can be selected to reinforce the effect of certain metrics). For each source, the TII provides an overall tsunami hazard intensity along the USEC coast that allows both a comparison among sources and a quantification of tsunami hazard as a function of the source return period. At the most impacted areas of the USEC (0.1 percentile), we find that tsunami hazard in the 100-500 year return period range is commensurate with that posed by category 3-5 tropical cyclones, taking into account the larger current velocities and forces caused by tsunami waves. Based on results of this work, high-resolution inundation PTHA maps will be developed in the future, similar to the PMT maps, in areas identified to have higher tsunami hazard, using more levels of nested grids, to achieve a 10-30 m resolution along the coast.

scholarly journals Relationships among the springtime ground–level NOx, O3 and NO3 in the vicinity of highways in the US East Coast

2011 ◽  
Vol 2 (3) ◽  
pp. 374-383 ◽  
Author(s):  
Fei Song ◽  
Jin Young Shin ◽  
Rafael Jusino‐Atresino ◽  
Yuan Gao
Keyword(s):  
East Coast ◽  
Ground Level ◽  
The Us ◽  
Us East Coast

scholarly journals A coastal hazards data base for the US East Coast

1992 ◽  
Author(s):  
V.M. Gornitz ◽  
T.W. White ◽  
R.C. Daniels
Keyword(s):  
Data Base ◽  
East Coast ◽  
Coastal Hazards ◽  
The Us ◽  
Us East Coast

Modeling coastal tsunami hazard from submarine mass failures: effect of slide rheology, experimental validation, and case studies off the US East Coast

2016 ◽  
Vol 86 (1) ◽  
pp. 353-391 ◽  
Author(s):  
Stéphan T. Grilli ◽  
Mike Shelby ◽  
Olivier Kimmoun ◽  
Guillaume Dupont ◽  
Dmitry Nicolsky ◽  
...  
Keyword(s):  
Case Studies ◽  
Experimental Validation ◽  
East Coast ◽  
Tsunami Hazard ◽  
The Us ◽  
Us East Coast

scholarly journals Predicting ocean waves along the US east coast during energetic winter storms: sensitivity to whitecapping parameterizations

Ocean Science ◽  
2019 ◽  
Vol 15 (3) ◽  
pp. 691-715 ◽  
Author(s):  
Mohammad Nabi Allahdadi ◽  
Ruoying He ◽  
Vincent S. Neary
Keyword(s):  
East Coast ◽  
Ocean Waves ◽  
Source Terms ◽  
Frequency Spectra ◽  
Winter Storms ◽  
Wave Parameters ◽  
The Us ◽  
Wind Input ◽  
Simulation Results ◽  
Us East Coast

Abstract. The performance of two methods for quantifying whitecapping dissipation incorporated in the Simulating Waves Nearshore (SWAN) wave model is evaluated for waves generated along and off the US east coast under energetic winter storms with a predominantly westerly wind. Parameterizing the whitecapping effect can be done using the Komen-type schemes, which are based on mean spectral parameters, or the saturation-based (SB) approach of van der Westhuysen (2007), which is based on local wave parameters and the saturation level concept of the wave spectrum (we use “Komen” and “Westhuysen” to denote these two approaches). Observations of wave parameters and frequency spectra at four National Data Buoy Center (NDBC) buoys are used to evaluate simulation results. Model–data comparisons show that when using the default parameters in SWAN, both Komen and Westhuysen methods underestimate wave height. Simulations of mean wave period using the Komen method agree with observations, but those using the Westhuysen method are substantially lower. Examination of source terms shows that the Westhuysen method underestimates the total energy transferred into the wave action equations, especially in the lower frequency bands that contain higher spectral energy. Several causes for this underestimation are identified. The primary reason is the difference between the wave growth conditions along the east coast during winter storms and the conditions used for the original whitecapping formula calibration. In addition, some deficiencies in simulation results are caused along the coast by the “slanting fetch” effect that adds low-frequency components to the 2-D wave spectra. These components cannot be simulated partly or entirely by available source terms (wind input, whitecapping, and quadruplet) in models and their interaction. Further, the effect of boundary layer instability that is not considered in the Komen and Westhuysen whitecapping wind input formulas may cause additional underestimation.

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