An Investigation of the Storm Surge of February 1, 1983 Using Numerical Models

2018 ◽  
pp. 43-72 ◽  
Author(s):  
Roger Proctor ◽  
Judith Wolf
Keyword(s):  
Storm Surge ◽  
Numerical Models

scholarly journals Assessing storm surge hazard and impact of sea level rise in the Lesser Antilles case study of Martinique

2017 ◽  
Vol 17 (9) ◽  
pp. 1559-1571 ◽  
Author(s):  
Yann Krien ◽  
Bernard Dudon ◽  
Jean Roger ◽  
Gael Arnaud ◽  
Narcisse Zahibo
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Storm Surge ◽  
Numerical Models ◽  
Lesser Antilles ◽  
Adaptation Measures ◽  
Worst Case ◽  
Mitigation And Adaptation ◽  
The Impact

Abstract. In the Lesser Antilles, coastal inundations from hurricane-induced storm surges pose a great threat to lives, properties and ecosystems. Assessing current and future storm surge hazards with sufficient spatial resolution is of primary interest to help coastal planners and decision makers develop mitigation and adaptation measures. Here, we use wave–current numerical models and statistical methods to investigate worst case scenarios and 100-year surge levels for the case study of Martinique under present climate or considering a potential sea level rise. Results confirm that the wave setup plays a major role in the Lesser Antilles, where the narrow island shelf impedes the piling-up of large amounts of wind-driven water on the shoreline during extreme events. The radiation stress gradients thus contribute significantly to the total surge – up to 100 % in some cases. The nonlinear interactions of sea level rise (SLR) with bathymetry and topography are generally found to be relatively small in Martinique but can reach several tens of centimeters in low-lying areas where the inundation extent is strongly enhanced compared to present conditions. These findings further emphasize the importance of waves for developing operational storm surge warning systems in the Lesser Antilles and encourage caution when using static methods to assess the impact of sea level rise on storm surge hazard.

scholarly journals Assessing storm surge hazard and impact of sea level rise in Lesser Antilles-Case study of Martinique

2017 ◽  
Author(s):  
Yann Krien ◽  
Bernard Dudon ◽  
Jean Roger ◽  
Gaël Arnaud ◽  
Narcisse Zahibo
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Storm Surge ◽  
Numerical Models ◽  
Lesser Antilles ◽  
Adaptation Measures ◽  
Worst Case ◽  
Mitigation And Adaptation ◽  
The Impact

Abstract. In the Lesser Antilles, coastal inundations from hurricane-induced storm surges cause great threats to lives, properties, and ecosystems. Assessing current and future storm surge hazard with sufficient spatial resolution is of primary interest to help coastal planners and decision makers develop mitigation and adaptation measures. Here, we use wave-current numerical models and statistical methods to investigate worst case scenarios and 100-year surge levels for the case study of Martinique, under present climate or considering a potential sea-level rise. Results confirm that the wave setup plays a major role in Lesser Antilles, where the narrow island shelf impedes the piling-up of large amounts of wind-driven water on the shoreline during extreme events. The radiation stress gradients thus contribute significantly to the total surge, up to 100 % in some cases. The non-linear interactions of sea level rise with bathymetry and topography are generally found to be relatively small in Martinique, but can reach several tens of centimeters in low-lying areas where the inundation extent is strongly enhanced compared to present conditions. These findings further emphasize the importance of waves for developing operational storm surge warning systems in the Lesser Antilles, and encourage caution when using static methods to assess the impact of sea level rise on storm surge hazard.

scholarly journals Storm Surge Hazard Assessment of the Levee of a Rapidly Developing City-Based on LiDAR and Numerical Models

2020 ◽  
Vol 12 (22) ◽  
pp. 3723 ◽  
Author(s):  
Qingrong Liu ◽  
Chengqing Ruan ◽  
Jingtian Guo ◽  
Jian Li ◽  
Xihu Lian ◽  
...  
Keyword(s):  
Storm Surge ◽  
Hazard Assessment ◽  
Point Cloud ◽  
Numerical Models ◽  
Ocean Model ◽  
Economic Losses ◽  
3D Point Cloud ◽  
Point Cloud Data ◽  
Disaster Prevention ◽  
Cloud Data

Rapidly developing cities could require an urgent hazard assessment to ensure the protection of their economy and population against natural disasters. However, these cities that have rapidly developed should have historical records of observations that are too short to provide sufficient data information for such an assessment. This study used ocean numerical models (i.e., Finite-Volume Community Ocean Model (FVCOM) and Parabolic Mild-Slope Wave Module (MIKE 21 PMS) to reconstruct data for a storm surge hazard assessment of the levee at Weifang (China). LiDAR (Light Detection and Ranging) data were also used to obtain 3D point cloud data and the structure of the levee. The designed levee height was calculated based on the simulations and 3D point cloud data, and the results were compared with measured heights to evaluate whether the levee is sufficiently high to satisfy the safety requirement. The findings of this work will enhance the marine disaster prevention capacity of the region and could help reduce economic losses associated with marine-related disasters. The results could also provide support for future work on disaster prevention in the field of coastal marine engineering.

scholarly journals FLOW COMPUTATIONS NEARBY A STORM SURGE BARRIER UNDER CONSTRUCTION WITH TWO-DIMENSIONAL NUMERICAL MODELS

1986 ◽  
Vol 1 (20) ◽  
pp. 143
Author(s):  
H.E. Klatter ◽  
J.M.C. Dijkzeul ◽  
G. Hartsuiker ◽  
L. Bijlsma
Keyword(s):  
Numerical Model ◽  
Storm Surge ◽  
Field Data ◽  
Numerical Models ◽  
Flow Patterns ◽  
Scale Model ◽  
Energy Losses ◽  
Local Energy ◽  
Two Dimensional ◽  
Physical Scale

This paper discusses the application of two-dimensional tidal models to the hydraulic research for the storm surge barrier in the Eastern Scheldt in the Netherlands. At the site of the barrier local energy losses dominate the flow. Three methods are discussed for dealing with these energy losses in a numerical model based on the long wave equations. The construction of the storm surge barrier provided extensive field data for various phases of the construction of the barrier and these field data are used as a test case for the computation at methods developed. One method is preferred since it gives good agreement between computations and field data. The two-dimensional flow patterns, the discharge and the head-difference agree well,, The results of scale model tests were also available for comparison. This comparison demonstrated that depth-averaged velocities, computed by a two-dimensional numerical model, are as accurate as values obtained from a large physical scale model. Even compicated flow patterns with local energy losses and sharp velocity gradients compared well.

scholarly journals Forecasting of Hazard Zone due to Storm Surge Using SIND Model

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Dong Hyun Kim ◽  
Hyung Ju Yoo ◽  
Seung Oh Lee
Keyword(s):  
Storm Surge ◽  
Governing Equation ◽  
Numerical Models ◽  
Shape Similarity ◽  
Short Term ◽  
Fast Calculation ◽  
Fem Method ◽  
Hazard Zone ◽  
Verification Process ◽  
Simulation Time

We have developed the SIND (scientific interpolation for natural disasters) model to forecast natural hazard zone for storm surge. Most previous studies have been conducted to predict hazard zone with numerical simulations based on various scenarios. It is hard to predict hazard zone for all scenarios and to respond immediately because most numerical models are requested a long simulation time and complicated postprocess, especially in coastal engineering. Thus, in this study, the SIND model was developed to overcome these limitations. The principal developing methods are the scientific interpolation for risk grades and trial and error for parameters embedded in the governing equation. Even designed with hatch files, applying disaster characteristics such as the risk propagation, the governing equation for storm surge in coastal lines was induced from the mathematical solver, COMSOL Multiphysics software that solves partial differential equations for multiple physics using FEM method. The verification process was performed through comparison with the official reference, and the accuracy was calculated with a shape similarity indicating the geometric similarity of the hazard zone. It was composed of position, shape, and area criteria. The accuracy of about 80% in terms of shape similarity was archived. The strength of the model is high accuracy and fast calculation time. It took only less than few seconds to create a hazard map for each scenario. As future works, if the characteristics of other disasters would be understood well, it would be able to present risk propagation induced from each natural disaster in a short term, which should help the decision making for EAP.

A (semi-)probabilistic storm surge EWS implementation for the Emilia-Romagna region (Italy)

2021 ◽  
Author(s):  
Luis Germano Biolchi ◽  
Silvia Unguendoli ◽  
Lidia Bressan ◽  
Beatrice Maria Sole Giambastiani ◽  
Andrea Valentini
Keyword(s):  
Sea Level ◽  
Storm Surge ◽  
Numerical Models ◽  
Mitigation Measures ◽  
Deterministic System ◽  
Emilia Romagna Region ◽  
The Mean ◽  
Coastal Risk ◽  
Sea Storm ◽  
The Eu

<p>The low lying and sandy coastal areas of the Emilia-Romagna region are heavily threatened by sea storms, often leading to flooding and coastal erosion events with severe impacts on citizens’ quality of life, damages to the cultural heritage and effects on economic activities (e.g. aquaculture, fisheries, tourism, beach facilities). Climate change projections reinforce the need of strategies and tools to prevent damages and promptly react to extreme events. In this context and in the framework of non-structural mitigation measures, the Hydro-Meteo-Climate Service of Arpae Emilia-Romagna (Arpae-SIMC) developed and operationally manages a Coastal Early Warning System (EWS) for the Emilia-Romagna Region (Northeast Italy).</p><p>The EWS was developed during the EU Project FP7-MICORE and it is a state-of-the-art coastal forecasting system that follows a chain of operational numerical models: the meteorological model COSMO, the wave model SWAN-MEDITARE, the ocean model AdriaROMS, and the morphodynamic model XBeach. The latter is currently implemented on a series of cross-shore beach profiles covering eight locations distributed along the Emilia-Romagna shore. Deterministic daily forecasts (72-hours) are generated and Storm Impact Indicators (SIIs) used to assess sea-storm induced coastal risk along the region’s littoral (geo.regione.emilia-romagna.it/schede/ews). </p><p>It is widely known that among the limitations of deterministic approaches, the lack of uncertainty estimation is often problematic as decision-makers might be misled if the only forecast available underestimates (or overestimates) incoming conditions. Hence, following the success of probabilistic forecasting in meteorological applications, storm surge EWSs following ensemble frameworks have been recently developed, allowing for more information available to sustain the decision-making process. Towards the new paradigm change, one of the foreseen outputs of the European Interreg Italy-Croatia CBC Programme project Strategic development of flood management (STREAM) involves the development of a “probabilistic EWS for coastal risk implemented and tested on at least one location along the Emilia-Romagna Coast”. </p><p>The initial implementation of the (semi-)probabilistic framework benefits from the EU ADRION I-STORMS (Integrated Sea Storm Management Strategies) project outcomes, in which wave and sea level multi-model ensembles were developed for the Adriatic Sea giving origin to the Transnational Multi-Model Ensemble (TMES). The TMES was made available as one of the six Integrated Web System (IWS) components, combining five wave and six sea level forecasting systems as means to provide 48-hour forecasts in terms of sea level and wave characteristics (Hs, Tm and Dm). Ensemble mean and standard deviation (SD) are calculated based on different forecasting systems’ results. In the initial approach, four TMES combinations have been tested as XBeach forcing: the TMES mean; the mean minus one SD; the mean plus one SD; the mean plus two SDs. Two months were analyzed together with the already implemented deterministic system for two profiles along the region’s coast.</p><p>The methodology followed for the test period will be shown as well as the results. Furthermore, the methodology under development will be also shown as means to enhance the discussion involving storm surge ensemble applications.</p>

scholarly journals Measuring Storm Surge with an Airborne Wide-Swath Radar Altimeter

2009 ◽  
Vol 26 (10) ◽  
pp. 2200-2215 ◽  
Author(s):  
C. W. Wright ◽  
E. J. Walsh ◽  
W. B. Krabill ◽  
W. A. Shaffer ◽  
S. R. Baig ◽  
...  
Keyword(s):  
Water Level ◽  
Storm Surge ◽  
Numerical Models ◽  
Surface Wind ◽  
Spatial Evolution ◽  
Radar Altimeter ◽  
Large Area ◽  
Tidal Variation ◽  
Hurricane Wind ◽  
Wide Swath

Abstract Over the years, hurricane track forecasts and storm surge models, as well the digital terrain and bathymetry data they depend on, have improved significantly. Strides have also been made in the knowledge of the detailed variation of the surface wind field driving the surge. The area of least improvement has been in obtaining data on the temporal/spatial evolution of the mound of water that the hurricane wind and waves push against the shore to evaluate the performance of the numerical models. Tide gauges in the vicinity of the landfall are frequently destroyed by the surge. Survey crews dispatched after the event provide no temporal information and only indirect indications of the maximum water level over land. The landfall of Hurricane Bonnie on 26 August 1998, with a surge less than 2 m, provided an excellent opportunity to demonstrate the potential benefits of direct airborne measurement of the temporal/spatial evolution of the water level over a large area. Despite a 160-m variation in aircraft altitude, an 11.5-m variation in the elevation of the mean sea surface relative to the ellipsoid over the flight track, and the tidal variation over the 5-h data acquisition interval, a survey-quality global positioning system (GPS) aircraft trajectory allowed the NASA scanning radar altimeter carried by a NOAA hurricane research aircraft to demonstrate that an airborne wide-swath radar altimeter could produce targeted measurements of storm surge that would provide an absolute standard for assessing the accuracy of numerical storm surge models.

scholarly journals A MULTI-MODEL APPROACH TO SIMULATE THE STORM SURGE AT PUERTO RICO DUE TO HURRICANES IRMA AND MARIA

2018 ◽  
pp. 56
Author(s):  
David F. Kelly ◽  
Ewelina Luczko ◽  
Michael Fullarton ◽  
Yahia Kala
Keyword(s):  
Puerto Rico ◽  
Storm Surge ◽  
State Of The Art ◽  
Numerical Models ◽  
Storm Surges ◽  
Wind Pressure ◽  
Governing Equations ◽  
Storm Tide ◽  
Long Wave ◽  
Model Approach

In this paper we present the results of a multimodel approach to simulating the recent storm surges due to hurricanes Irma and Maria. The study focuses on Puerto Rico which, as a consequence of hurricane Maria, experienced storm surge around the entire perimeter of the island. In this study the storm tide is modeled using a variety of state-of-the-art 2DH numerical models. All models are based on the long wave assumption and employ the Non-Linear Shallow Water (NLSW) equations. The models vary according to the form of the governing NLSW equations that they employ. Differences include linearization and primitive variable or conserved variable (divergence) form. The numerical solution techniques used to solve the governing equations, as well as the options available for the wind, pressure, tidal forcing terms and wetting/drying techniques also vary between (and within) the models.

scholarly journals Compound Hydrometeorological Extremes: Drivers, Mechanisms and Methods

2021 ◽  
Vol 9 ◽  
Author(s):  
Wei Zhang ◽  
Ming Luo ◽  
Si Gao ◽  
Weilin Chen ◽  
Vittal Hari ◽  
...  
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Statistical Modeling ◽  
Storm Surge ◽  
Climate Models ◽  
Heat Waves ◽  
Numerical Models ◽  
Global Climate ◽  
The State ◽  
Global Climate Models

Compound extremes pose immense challenges and hazards to communities, and this is particularly true for compound hydrometeorological extremes associated with deadly floods, surges, droughts, and heat waves. To mitigate and better adapt to compound hydrometeorological extremes, we need to better understand the state of knowledge of such extremes. Here we review the current advances in understanding compound hydrometeorological extremes: compound heat wave and drought (hot-dry), compound heat stress and extreme precipitation (hot-wet), cold-wet, cold-dry and compound flooding. We focus on the drivers of these extremes and methods used to investigate and quantify their associated risk. Overall, hot-dry compound extremes are tied to subtropical highs, blocking highs, atmospheric stagnation events, and planetary wave patterns, which are modulated by atmosphere-land feedbacks. Compared with hot-dry compound extremes, hot-wet events are less examined in the literature with most works focusing on case studies. The cold-wet compound events are commonly associated with snowfall and cold frontal systems. Although cold-dry events have been found to decrease, their underlying mechanisms require further investigation. Compound flooding encompasses storm surge and high rainfall, storm surge and sea level rise, storm surge and riverine flooding, and coastal and riverine flooding. Overall, there is a growing risk of compound flooding in the future due to changes in sea level rise, storm intensity, storm precipitation, and land-use-land-cover change. To understand processes and interactions underlying compound extremes, numerical models have been used to complement statistical modeling of the dependence between the components of compound extremes. While global climate models can simulate certain types of compound extremes, high-resolution regional models coupled with land and hydrological models are required to simulate the variability of compound extremes and to project changes in the risk of such extremes. In terms of statistical modeling of compound extremes, previous studies have used empirical approach, event coincidence analysis, multivariate distribution, the indicator approach, quantile regression and the Markov Chain method to understand the dependence, greatly advancing the state of science of compound extremes. Overall, the selection of methods depends on the type of compound extremes of interests and relevant variables.

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