Storm Surge Model Research Articles

An Integrated Scenario Ensemble-Based Framework for Hurricane Evacuation Modeling: Part 2-Hazard Modeling.

Hurricane track and intensity can change rapidly in unexpected ways, thus making predictions of hurricanes and related hazards uncertain. This inherent uncertainty often translates into suboptimal decision-making outcomes, such as unnecessary evacuation. Representing this uncertainty is thus critical in evacuation planning and related activities. We describe a physics-based hazard modeling approach that (1) dynamically accounts for the physical interactions among hazard components and (2) captures hurricane evolution uncertainty using an ensemble method. This loosely coupled model system provides a framework for probabilistic water inundation and wind speed levels for a new, risk-based approach to evacuation modeling, described in a companion article in this issue. It combines the Weather Research and Forecasting (WRF) meteorological model, the Coupled Routing and Excess STorage (CREST) hydrologic model, and the ADvanced CIRCulation (ADCIRC) storm surge, tide, and wind-wave model to compute inundation levels and wind speeds for an ensemble of hurricane predictions. Perturbations to WRF's initial and boundary conditions and different model physics/parameterizations generate an ensemble of storm solutions, which are then used to drive the coupled hydrologic + hydrodynamic models. Hurricane Isabel (2003) is used as a case study to illustrate the ensemble-based approach. The inundation, river runoff, and wind hazard results are strongly dependent on the accuracy of the mesoscale meteorological simulations, which improves with decreasing lead time to hurricane landfall. The ensemble envelope brackets the observed behavior while providing "best-case" and "worst-case" scenarios for the subsequent risk-based evacuation model.

Using Satellite Altimetry to Calibrate the Simulation of Typhoon Seth Storm Surge off Southeast China

Satellite altimeters can capture storm surges generated by typhoons and tropical storms, if the satellite flies over at the right time. In this study, we show TOPEX/Poseidon altimeter-observed storm surge features off Southeast China on 10 October 1994 during Typhoon Seth. We then use a three-dimensional, barotropic, finite-volume community ocean model (FVCOM) to simulate storm surges. An innovative aspect is that satellite data are used to calibrate the storm surge model to improve model performance, by adjusting model wind forcing fields (the National Center for Environment Prediction (NCEP) reanalysis product) in reference to the typhoon best-track data. The calibration reduces the along-track root-mean-square (RMS) difference between model and altimetric data from 0.15 to 0.10 m. It also reduces the RMS temporal difference from 0.21 to 0.18 m between the model results and independent tide-gauge data at Xiamen. In particular, the calibrated model produces a peak storm surge of 1.01 m at 6:00 10 October 1994 at Xiamen, agreeing with tide-gauge data; while the peak storm surge with the NCEP forcing is 0.71 m only. We further show that the interaction between storm surges and astronomical tides contributes to the peak storm surge by 34% and that the storm surge propagates southwestward as a coastally-trapped Kelvin wave.

Hydrodynamic storm surge model simplification via application of land to water isopleths in coastal Louisiana

The Mississippi River Delta ranks the seventh largest delta in the world. It provides a habitat for the Louisiana seafood industry, navigation canals and rivers that support five of the 15 largest cargo ports by volume in the United States, and hurricane storm surge protection for coastal cities and oil and gas industry infrastructure that facilitates 90% of the outer continental oil and gas extraction. Due to substantial coastal wetland loss since 1900, the risk of damage to these industries and infrastructure has increased through time. The goal of this research is to develop a methodology to analyze the historical and future evolution of coastal hazards, such as hurricane storm surge, across a complex, low-lying coastal landscape. To accomplish this task, the change in coastal hazards is analyzed through historical changes in coastal wetlands. Specifically, isopleths, defined as lines on a map indicating a constant value of a given variable, are developed to describe areas of constant values of the ratio of land to water (L:W) across coastal Louisiana.In this analysis, a methodology is developed that utilizes land to water (L:W) isopleths to simplify the modern day Louisiana coastal landscape as represented in a state-of-the-art high resolution storm surge model. L:W isopleths are derived for the year 2010 and used to construct 36 storm surge models, each featuring variations of three distinct coastal zones: “High” (i.e. high wetland), “Intermediate” (i.e. wetland), and “Submersed” (i.e. region between open water and wetland). The ADvanced CIRCulation (ADCIRC) code is used to compute water surface elevations and depth-averaged currents forced by hurricane wind and pressures from Hurricanes Rita, Gustav, and Katrina for each model. Peak water levels and volume of inundation are quantified within hydrologic unit code watersheds (HUC12) in order to compare storm surge models featuring high resolution and simplified coastal landscapes.A L:W isopleth permutation of 99%–90%–40%–1% with areas labeled “High” (99%–90%), “Intermediate” (90%–40%) and “Submersed” (40%–1%) is found to best represent simulated storm surge that most closely reproduces the high resolution storm surge model. Simulation results reveal the methodology developed in this analysis is effective in identifying an isopleth permutation that accurately simplifies a high resolution storm surge model. This result may lead to future analyses of the historical evolution of storm surge attenuation in the Mississippi River Delta (MRD) as well as other complex, low-lying deltas. These possibilities include developing storm surge models for the years 1930 and 1970, for instance, with the same isopleth permutation to examine the changes in storm surge attenuation through time. This analysis could also be applied in other similar low-lying coastal regions to conduct past and future analyses of the evolution of coastal hazards.

The mapping of storm surge-prone areas and characterizing surge-producing cyclones in Leyte Gulf, Philippines

Historically, Leyte Gulf in central eastern Philippines has received catastrophic damage due to storm surges, the most recent of which was during Typhoon Haiyan in 2013. A city-level risk assessment was performed on Leyte Gulf through synthetic storm generation, high-resolution ocean modeling, and decision tree analyses. Cyclones were generated through a combination of a Poisson point process and Monte Carlo simulations. Wind and pressure fields generated from the cyclones were used in a storm surge model of Leyte Gulf developed on Delft3D. The output of these simulations was a synthetic record of extreme sea level events, which were used to estimate maximum surge heights for different return periods and to characterize surge-producing storm characteristics using decision tree analyses. The results showed that the area most prone to surges is the Tacloban–Basey area with a 2.8 ± 0.3 m surge occurring at a frequency of every 50 years. Nearby Palo area will likely receive a surge of 1.9 ± 0.4 m every 50 years while Giporlos–Salcedo area a surge of 1.0 ± 0.1 m. The decision tree analysis performed for each of these areas showed that for surges of 3–4 m, high-velocity winds (> 30 m/s) are consistently the main determining factor. For the areas, Tacloban, Basey, and Giporlos–Salcedo, wind speed was also the main determining factor for surge > 4 m.

Risk assessment of storm surge disaster based on numerical models and remote sensing

Storm surge is one of the most serious ocean disasters in the world. Risk assessment of storm surge disaster for coastal areas has important implications for planning economic development and reducing disaster losses. Based on risk assessment theory, this paper uses coastal hydrological observations, a numerical storm surge model and multi-source remote sensing data, proposes methods for valuing hazard and vulnerability for storm surge and builds a storm surge risk assessment model. Storm surges in different recurrence periods are simulated in numerical models and the flooding areas and depth are calculated, which are used for assessing the hazard of storm surge; remote sensing data and GIS technology are used for extraction of coastal key objects and classification of coastal land use are identified, which is used for vulnerability assessment of storm surge disaster. The storm surge risk assessment model is applied for a typical coastal city, and the result shows the reliability and validity of the risk assessment model. The building and application of storm surge risk assessment model provides some basis reference for the city development plan and strengthens disaster prevention and mitigation.

Dynamic Modeling of Surface Runoff and Storm Surge during Hurricane and Tropical Storm Events

Hurricane events combine ocean storm surge penetration with inland runoff flooding. This article presents a new methodology to determine coastal flood levels caused by the combination of storm surge and surface runoff. The proposed approach couples the Simulating Waves Nearshore model and the Advanced Circulation (ADCIRC) model with the Gridded Surface Subsurface Hydrologic Analysis (GSSHA) two-dimensional hydrologic model. Radar precipitation data in a 2D hydrologic model with a circulation model allows simulation of time and spatially varied conditions. The method was applied to study flooding scenarios occurring during the passage of Hurricane Georges (1998) on the east coast of Puerto Rico. The combination of storm surge and surface runoff produced a critical scenario, in terms of flood depth, at this location. The paper describes the data collection process, circulation and hydrologic models, their assemblage and simulation scenarios. Results show that peak flow from inland runoff and peak flow due to storm surge did not coincide in the coastal zone; however, the interaction of both discharges causes an aggravated hazardous condition by increasing flood levels beyond those obtained with storm surge penetration only. Linking of storm surge and hydrologic models are necessary when storm surge conditions occur simultaneously with high precipitation over steep and small coastal watersheds.

Extreme storm surge modelling in the North Sea

This study shows that storm surge model performance in the North Sea is mostly unaffected by the application of temporal variations of surface drag due to changes in sea state provided the choice of a suitable constant Charnock parameter in the sea-state-independent case. Including essential meteorological features on smaller scales and minimising interpolation errors by increasing forcing data resolution are shown to be more important for the improvement of model performance particularly at the high tail of the probability distribution. This is found in a modelling study using WAQUA/DCSMv5 by evaluating the influence of a realistic air-sea momentum transfer parameterization and comparing it to the influence of changes in the spatial and temporal resolution of the applied forcing fields in an effort to support the improvement of impact and climate analysis studies. Particular attention is given to the representation of extreme water levels over the past decades based on the example of the Netherlands. For this, WAQUA/DCSMv5 is forced with ERA-Interim reanalysis data. Model results are obtained from a set of different forcing fields, which either (i) include a wave-state-dependent Charnock parameter or (ii) apply a constant Charnock parameter (α C h = 0.032) tuned for young sea states in the North Sea, but differ in their spatial and/or temporal resolution. Increasing forcing field resolution from roughly 79 to 12 km through dynamically downscaling can reduce the modelled low bias, depending on coastal station, by up to 0.25 m for the modelled extreme water levels with a 1-year return period and between 0.1 m and 0.5 m for extreme surge heights.

Impact of Phase III Project of Maji Mountain Port on sediment siltation in adjacent sea area

Based on a 3-D Finite Volume Coastal Ocean Model (FVCOM), tidal dynamics has been studied in the sea area around the Phase III Project of Maji Mountain Port (MMP). Furthermore, taking typhoon “Canhong” as an example, a storm surge and sediment model has also been established to study the impact of the Phase III Project on current flows and siltation during extreme weather. Tidal currents before and after the project have been compared. Model results show that the changes of tidal current mainly occur in the engineering areas with a magnitude change of 0.3–0.4 m/s during maximum flood and ebb tides. The flow condition for the port has been improved as the flow direction is changed to parallel to the wharf after the completion of the project. There is little siltation in the adjacent area, which will not affect the safety of ship navigation. Besides, the sudden siltation during typhoon period is relatively weak. The back silting in two days is less than 5 cm indicating no sudden siltation occurs.

The Practical Predictability of Storm Tide from Tropical Cyclones in the Gulf of Mexico

The potential for storm surge to cause extensive property damage and loss of life has increased urgency to more accurately predict coastal flooding associated with landfalling tropical cyclones. This work investigates the sensitivity of coastal inundation from storm tide (surge + tide) to four hurricane parameters—track, intensity, size, and translation speed—and the sensitivity of inundation forecasts to errors in forecasts of those parameters. An ensemble of storm tide simulations is generated for three storms in the Gulf of Mexico, by driving a storm surge model with best track data and systematically generated perturbations of storm parameters from the best track. The spread of the storm perturbations is compared to average errors in recent operational hurricane forecasts, allowing sensitivity results to be interpreted in terms of practical predictability of coastal inundation at different lead times. Two types of inundation metrics are evaluated: point-based statistics and spatially integrated volumes. The practical predictability of surge inundation is found to be limited foremost by current errors in hurricane track forecasts, followed by intensity errors, then speed errors. Errors in storm size can also play an important role in limiting surge predictability at short lead times, due to observational uncertainty. Results show that given current mean errors in hurricane forecasts, location-specific surge inundation is predictable for as little as 12–24 h prior to landfall, less for small-sized storms. The results also indicate potential for increased surge predictability beyond 24 h for large storms by considering a storm-following, volume-integrated metric of inundation.

Evaluation of weather forecast systems for storm surge modeling in the Chesapeake Bay

Accurate forecast of sea-level heights in coastal areas depends, among other factors, upon a reliable coupling of a meteorological forecast system to a hydrodynamic and wave system. This study evaluates the predictive skills of the coupled circulation and wind-wave model system (ADCIRC+SWAN) for simulating storm tides in the Chesapeake Bay, forced by six different products: (1) Global Forecast System (GFS), (2) Climate Forecast System (CFS) version 2, (3) North American Mesoscale Forecast System (NAM), (4) Rapid Refresh (RAP), (5) European Center for Medium-Range Weather Forecasts (ECMWF), and (6) the Atlantic hurricane database (HURDAT2). This evaluation is based on the hindcasting of four events: Irene (2011), Sandy (2012), Joaquin (2015), and Jonas (2016). By comparing the simulated water levels to observations at 13 monitoring stations, we have found that the ADCIR+SWAN System forced by the following: (1) the HURDAT2-based system exhibited the weakest statistical skills owing to a noteworthy overprediction of the simulated wind speed; (2) the ECMWF, RAP, and NAM products captured the moment of the peak and moderately its magnitude during all storms, with a correlation coefficient ranging between 0.98 and 0.77; (3) the CFS system exhibited the worst averaged root-mean-square difference (excepting HURDAT2); (4) the GFS system (the lowest horizontal resolution product tested) resulted in a clear underprediction of the maximum water elevation. Overall, the simulations forced by NAM and ECMWF systems induced the most accurate results best accuracy to support water level forecasting in the Chesapeake Bay during both tropical and extra-tropical storms.

Impact of Cyclone Track Features and Tidal Phase Shift upon Surge Characteristics in the Bay of Bengal along the Bangladesh Coast

The impact of cyclone track features (e.g., cyclone translation speed, cyclone path and cyclone landfall crossing angle) in combination with tidal phase shift upon surge characteristics have been investigated at the Bay of Bengal along the Bangladesh coast. A two-dimensional hydrodynamic model in a horizontal direction (2DH) coupled with a storm-surge model has been employed for the study. Numerical experiments with three different cyclone translation speeds show that when the surge height is directly forced by the cyclonic wind speed especially within the RWM (Radius of Maximum Wind), faster translation speed produces reduced surge height as the cyclone gets less time to force the water. On the other hand, at locations outside the RMW, surge waves travel as a propagating long wave where higher surges are produced by faster moving cyclones. It is found that surge arrival times are more and more affected by tidal phase when cyclone translation speed is reduced. Analysis of seven hypothetical parallel cyclone paths show that local bathymetry and complex coastline configurations strongly influence the surge height and surge arrival time along the Bangladesh coast. From the analyses of cyclone landfall crossing angles at the Khulna and Chittagong coasts, it is observed that surge durations are the smallest at both the coasts when the coastline crossing angles are the smallest.

Numerical Modeling of Coastal Storms for Ice-Free and Ice-Covered Lake Erie

ABSTRACT Farhadzadeh, A. and Gangai, J., 2017. Numerical modeling of coastal storms for ice-free and ice-covered Lake Erie. Lake Erie is the shallowest among the Great Lakes. Because of its shallow depth and because predominant wind direction in the area is along the lake's longitudinal axis, eastern and western Lake Erie experience significant storm surge that are usually followed by seiches. The lake warms in summer and quickly freezes over in winter when it often develops extensive surface ice. The surface ice, in turn, can modify wind setup and waves and even hinder wave propagation in areas where the surface ice is densely concentrated. In the following, a coupled numerical model for storm surge and wave is utilized for the simulation of Lake Erie coastal storms under ice-free and ice-covered lake conditions. Six extreme events, affecting both eastern and western Lake Erie, are selected for presentation here. A high resolution mesh is developed using the National Oceanic and Atmospheric Administratio...

Development of a cylindrical polar coordinates shallow water storm surge model for the coast of Bangladesh

The coast of Bangladesh is funnel shaped. The narrowing of the Meghna estuary along with its peculiar topography creates a funneling effect that has a large impact on surge response. In order to have an accurate estimation of surge levels, the impacts of the estuary should be treated with due importance. To represent in detail the real complexities of the estuary, a very high resolution is required, which in turn necessitates more computational cost. Considering the facts into account, a location specific vertically integrated shallow water model in cylindrical polar coordinates is developed in this study to foresee water levels associated with a storm. A one-way nested grid technique is used to incorporate coastal complicities with minimum cost. In specific, a fine mesh scheme (FMS) capable of incorporating coastal complexities with acceptable accuracy is nested into a coarse mesh scheme (CMS) covering up to 15∘N latitude in the Bay of Bengal. The coastal and island boundaries are approximated through appropriate stair step representation and the model equations are solved by a conditionally stable semi-implicit finite difference technique using a structured C-grid. Numerical experiments are performed using the model to estimate water levels due to surge associated with the April 1991 and AILA, 2009 cyclones, which struck the coast of Bangladesh. Time series of tidal level is generated from an available tide table through a cubic spline interpolation method. The computed surge response is superimposed linearly with the generated time series of tidal oscillation to obtain the time series of total water levels. The model results exhibit a good agreement with observation and reported data.

Deep Uncertainties in Sea-Level Rise and Storm Surge Projections: Implications for Coastal Flood Risk Management.

Sea levels are rising in many areas around the world, posing risks to coastal communities and infrastructures. Strategies for managing these flood risks present decision challenges that require a combination of geophysical, economic, and infrastructure models. Previous studies have broken important new ground on the considerable tensions between the costs of upgrading infrastructure and the damages that could result from extreme flood events. However, many risk-based adaptation strategies remain silent on certain potentially important uncertainties, as well as the tradeoffs between competing objectives. Here, we implement and improve on a classic decision-analytical model (Van Dantzig 1956) to: (i) capture tradeoffs across conflicting stakeholder objectives, (ii) demonstrate the consequences of structural uncertainties in the sea-level rise and storm surge models, and (iii) identify the parametric uncertainties that most strongly influence each objective using global sensitivity analysis. We find that the flood adaptation model produces potentially myopic solutions when formulated using traditional mean-centric decision theory. Moving from a single-objective problem formulation to one with multiobjective tradeoffs dramatically expands the decision space, and highlights the need for compromise solutions to address stakeholder preferences. We find deep structural uncertainties that have large effects on the model outcome, with the storm surge parameters accounting for the greatest impacts. Global sensitivity analysis effectively identifies important parameter interactions that local methods overlook, and that could have critical implications for flood adaptation strategies.

Non-Tidal Ocean Loading Correction for the Argentinean-German Geodetic Observatory Using an Empirical Model of Storm Surge for the Río de la Plata

The Argentinean-German Geodetic Observatory is located 13 km from the Rio de la Plata, in an area that is frequently affected by storm surges that can vary the level of the river over ±3 m. Water-level information from seven tide gauge stations located in the Rio de la Plata are used to calculate every hour an empirical model of water heights (tidal + non-tidal component) and an empirical model of storm surge (non-tidal component) for the period 01/2016–12/2016. Using the SPOTL software, the gravimetric response of the models and the tidal response are calculated, obtaining that for the observatory location, the range of the tidal component (3.6 nm/s2) is only 12% of the range of the non-tidal component (29.4 nm/s2). The gravimetric response of the storm surge model is subtracted from the superconducting gravimeter observations, after applying the traditional corrections, and a reduction of 7% of the RMS is obtained. The wavelet transform is applied to the same series, before and after the non-tidal correction, and a clear decrease in the spectral energy in the periods between 2 and 12 days is identify between the series. Using the same software East, North and Up displacements are calculated, and a range of 3, 2, and 11 mm is obtained, respectively. The residuals obtained after applying the non-tidal correction allow to clearly identify the influence of rain events in the superconducting gravimeter observations, indicating the need of the analysis of this, and others, hydrological and geophysical effects.

CaMEL and ADCIRC Storm Surge Models—A Comparative Study

The Computation and Modeling Engineering Laboratory (CaMEL), an implicit solver-based storm surge model, has been extended for use on high performance computing platforms. An MPI (Message Passing Interface) based parallel version of CaMEL has been developed from the previously existing serial version. CaMEL uses hybrid finite element and finite volume techniques to solve shallow water conservation equations in either a Cartesian or a spherical coordinate system and includes hurricane-induced wind stress and pressure, bottom friction, the Coriolis effect, and tidal forcing. Both semi-implicit and fully-implicit time stepping formulations are available. Once the parallel implementation is properly validated, CaMEL is evaluated against ADCIRC, an established storm surge model, using a hindcast of storm surge due to Hurricane Katrina. Observed high water marks are used to verify that both models have comparable accuracy. The effects of time step on the stability and accuracy of the models are investigated and indicate that the semi- and fully-implicit solvers in CaMEL allow the use of larger timesteps than ADCIRC’s explicit and semi-implicit solvers. However, ADCIRC outperforms CaMEL in parallel scalability and execution wall clock times. Wall times of CaMEL improve significantly when the largest stable time step sizes are used in respective models, although ADCIRC still is faster.

Storm surge characteristics and extreme parameters in the Chengshantou sea area

Storm surge in the Chengshantou sea area is simulated by the advanced circulation (ADCIRC) model. The Regional Atmospheric Modeling System (RAMS) wind model is used to simulate wind parameters used to be wind force of storm surge model. The comparison results of storm surges show good agreement between simulations and observations. The storm surge is caused by typhoon in summer but extratropical cyclone in winter. By statistical analysis of storm surge in 20 years, it is found that the annual max negative storm surge are all caused by extratropical cyclone while the frequency of annual max positive storm surge caused by tropical cyclone is about 20%. The extreme parameters are estimated by Gumbel distribution. The positive extreme storm surge of 100 year return period is determined as 95 cm and the negative is -124 cm.

A variable resolution right TIN approach for gridded oceanographic data

Many oceanographic applications require multi resolution representation of gridded data such as for bathymetric data. Although triangular irregular networks (TINs) allow for variable resolution, they do not provide a gridded structure. Right TINs (RTINs) are compatible with a gridded structure. We explored the use of two approaches for RTINs termed top-down and bottom-up implementations. We illustrate why the latter is most appropriate for gridded data and describe for this technique how the data can be thinned. While both the top-down and bottom-up approaches accurately preserve the surface morphology of any given region, the top-down method of vertex placement can fail to match the actual vertex locations of the underlying grid in many instances, resulting in obscured topology/bathymetry. Finally we describe the use of the bottom-up approach and data thinning in two applications. The first is to provide thinned, variable resolution bathymetry data for tests of storm surge and inundation modeling, in particular hurricane Katrina. Secondly we consider the use of the approach for an application to an oceanographic data grid of 3-D ocean temperature.

Circulation, dispersion and hydrodynamic connectivity over the Scotian Shelf and adjacent waters

A nested-grid ocean circulation modelling system is used in this study to examine the circulation of surfacewaters over the Scotian Shelf and its adjacent coastal water bodies. The modelling system consists of acoarse-resolution (1/12°) barotropic storm surge (outer) model covering the northwest Atlantic Ocean, and afine-resolution (1/16°) baroclinic (inner) model covering the Gulf of St. Lawrence, Scotian Shelf, and Gulf of Maine.The three-dimensional model currents are used to track trajectories of particles using a Lagrangian particle-trackingmodel. The simulated particle movements and distributions are used to examine the dispersion, retention, andhydrodynamic connectivity of surface waters over the study region. The near-surface dispersion is relatively high overwestern Cabot Strait, the inner Scotian Shelf, and the shelf break of the Scotian Shelf. The dispersion is relatively low inNorthumberland Strait. A process study is conducted to examine the physical processes affecting the surface dispersion,including tidal forcing and local wind forcing. The model results show that the tidal currents significantly influence thedispersion of surface waters in the Bay of Fundy.

Storm Surge along the Yellow River Delta under Directional Extreme Wind Conditions

ABSTRACT Wang, Z.; Zhou, L.; Li, Q., and Sun, X., 2017. Storm surge along the Yellow River Delta under directional extreme wind conditions. In: Zhi, Y. and Guido Aldana, P.A. (eds.), Sustainability of Water Resources and the Development of Coastal Environments: Select Proceedings from the 2016 International Conference on Water Resource and Environment (WRE2016). Journal of Coastal Research, Special Issue No. 80, pp. 86–91. Coconut Creek (Florida), ISSN 0749-0208. The storm surge model ADCIRC is applied to simulate storm surges along the Yellow River Delta. The wind force applied in this study was simulated by meteorological model MM5. Wind speed in storm surges among simulations and station observations were compared to verify consistency between simulations and real storm surges. The directional extreme wind parameters were studied in areas near the Yellow River Delta and determined by Pearson-III distribution. From these parameters, three typical storm surges forced by relative directional extreme wind ...