Storm Surge Model Research Articles

Joint effects of storm surge and sea-level rise on US Coasts: new economic estimates of impacts, adaptation, and benefits of mitigation policy

Recent literature, the US Global Change Research Program’s National Climate Assessment, and recent events, such as Hurricane Sandy, highlight the need to take better account of both storm surge and sea-level rise (SLR) in assessing coastal risks of climate change. This study combines three models—a tropical cyclone simulation model; a storm surge model; and a model for economic impact and adaptation—to estimate the joint effects of storm surge and SLR for the US coast through 2100. The model is tested using multiple SLR scenarios, including those incorporating estimates of dynamic ice-sheet melting, two global greenhouse gas (GHG) mitigation policy scenarios, and multiple general circulation model climate sensitivities. The results illustrate that a large area of coastal land and property is at risk of damage from storm surge today; that land area and economic value at risk expands over time as seas rise and as storms become more intense; that adaptation is a cost-effective response to this risk, but residual impacts remain after adaptation measures are in place; that incorporating site-specific episodic storm surge increases national damage estimates by a factor of two relative to SLR-only estimates, with greater impact on the East and Gulf coasts; and that mitigation of GHGs contributes to significant lessening of damages. For a mid-range climate-sensitivity scenario that incorporates dynamic ice sheet melting, the approach yields national estimates of the impacts of storm surge and SLR of $990 billion through 2100 (net of adaptation, cumulative undiscounted 2005$); GHG mitigation policy reduces the impacts of the mid-range climate-sensitivity estimates by $84 to $100 billion.

Mitigation of ECMWF–scatterometer wind biases in view of storm surge applications in the Adriatic Sea

The Adriatic Sea, a semi-enclosed sea extending about 900km by 200km and entirely surrounded by mountain chains, is subjected to high water levels produced essentially by the wind blowing along its major axis (sirocco). The operational storm surge models use the forecast fields produced by ECMWF atmospheric model as meteorological forcing. Recent works showed that in small basins surrounded by steep orography the ECMWF model underestimates the wind. This may introduce inaccuracies in forecasting the water level. Experiments conducted in the framework of the “Storm Surge for Venice” (eSurge-Venice) project, funded by the European Space Agency Data User Element program, were aimed to improve the operational forecasting of storm surge in the Northern Adriatic Sea by using satellite observations.The paper presents a methodology aimed to mitigate the ECMWF model underestimate of the sea surface wind by a tuning procedure based on the scatterometer-model wind speed and direction biases. The mitigation takes into account the spatial characteristics of the biases and is time dependent. This method globally reduces the model underestimate of the surface wind, handling the different areas of the basin differently, according to the spatial structure of the bias. The methodology is applied and verified over thirty-three test cases. It may be considered a tool to improve the present high water level forecast, waiting for the advent of convincing methodologies for scatterometer wind assimilation into the regional atmospheric models.

Numerical experiments of storm winds, surges, and waves on the southern coast of Korea during Typhoon Sanba: the role of revising wind force

Abstract. The southern coastal area of Korea has often been damaged by storm surges and waves due to the repeated approach of strong typhoons every year. The integrated model system is applied to simulate typhoon-induced winds, storm surges, and surface waves in this region during Typhoon Sanba in 2012. The TC96 planetary boundary layer wind model is used for atmospheric forcing and is modified to incorporate the effect of the land's roughness on the typhoon wind. Numerical experiments are carried out to investigate the effects of land-dissipated wind on storm surges and waves using the three-dimensional, unstructured grid, Finite Volume Coastal Ocean Model (FVCOM), which includes integrated storm surge and wave models with highly refined grid resolutions along the coastal region of complex geometry and topography. Compared to the measured data, the numerical models have successfully simulated storm winds, surges, and waves. Better agreement between the simulated and measured storm winds has been found when considering the effect of wind dissipation by land roughness. In addition, this modified wind force leads to clearly improved results in storm surge simulations, whereas the wave results have shown only slight improvement. The study results indicate that the effect of land dissipation on wind force plays a significant role in the improvement of water level modeling inside coastal areas.

PARAMETERIZATION OF COUPLED AIR-SEA INTERACTION FOR STORM SURGE AND OCEAN CURRENT STRUCTURE MODELING

There are many researches and development for the coupled atmosphere, ocean and wave model due to the improvement of the models. On the other hand, the vigorous observations for the momentum transport between the atmosphere and ocean were carried out due to reconsider the bulk formulas for coupling model. A lot of formulas depending on the wind speed or on the wave information are proposed. Although a coupling model is useful for tropical cyclone assessment for coastal engineers, the parameterization at the air-sea interface give strong influence on storm surge modeling. In this study, the influences of the bulk formulas to ocean and wave models using the atmosphere-ocean-wave coupling model are examined.

A time-dependent surrogate model for storm surge prediction based on an artificial neural network using high-fidelity synthetic hurricane modeling

Expedient prediction of storm surge is required for emergency managers to make critical decisions for evacuation, structure closure, and other emergency responses. However, time-dependent storm surge models do not exist for fast and accurate prediction in very short periods on the order of seconds to minutes. In this paper, a time-dependent surrogate model of storm surge is developed based on an artificial neural network with synthetic simulations of hurricanes. The neural network between six input hurricane parameters and one target parameter, storm surge, is trained by a feedforward backpropagation algorithm at each of 92 uniform time steps spanning 45.5 h for each storm. The basis data consist of 446 tropical storms developed from a joint probability model that was based on historical tropical storm activity in the Gulf of Mexico. Each of the 446 storms was modeled at high fidelity using a coupled storm surge and nearshore wave model. Storm surge is predicted by the 92 trained networks for approaching hurricane climatological and track parameters in a few seconds. Furthermore, the developed surrogate model is validated with measured data and high-fidelity simulations of two historical hurricanes at four points in southern Louisiana. In general, the neural networks at or near the boundary between land and ocean are well trained and model predictions are of similar accuracy to the basis modeling suites. Networks based on modeling results from complex inland locations are relatively poorly trained.

Storm-Surge Hindcast at Viana do Castelo: An Oceanic and Estuarine Domain Approach

Marujo, N.R.C.S.; Araújo, M.A.V.C., Trigo-Teixeira, A.; Falcão, A.P., and Mazzolari, A., 2014. Storm-surge hindcast at Viana do Castelo: An oceanic and estuarine domain approach.In the present work a storm-surge event, which occurred in Viana do Castelo (Portugal) on 14–17 October 1987, is modelled using the advanced circulation model (ADCIRC) . The main purpose of the work is to investigate the ability of ADCIRC to model storm-surge events in the region. Modelling this type of phenomena is of the utmost importance to comply with the European Union directive 2007/60/CE, concerning the assessment and risk management of floods, and to create risk charts used in coastal zone management. During this process, a strong emphasis was given to model calibration before storm-surge modelling. Preceding model calibration a field survey, using global navigation satellite system techniques, was carried out in the Lima Estuary to acquire lacking information required to build the corresponding digital terrain model (DTM). While modelling storm surge, two different domains were considered: a large oceanic and a smaller estuarine. For each of these domains, the model was calibrated with astronomy forcing using, respectively, the 6 and 10 most important tidal constituents, which were determined by harmonic analysis of the Viana do Castelo tidal gauge record. The friction coefficient, wave continuity, and lateral viscosity parameters were changed with this aim. Although the friction coefficient proved to be the most important calibration parameter, the other parameters are also important to achieve stable simulations. For the oceanic domain, the obtained results were improved by considering a variable Coriolis factor. Once the model was calibrated, it was forced using astronomy and meteorology jointly and separately. Atmospheric pressure, wind, and, for the estuarine domain, also river flow were considered as meteorological agents. The storm event was satisfactorily reproduced by the model and it was concluded that meteorology and astronomical effects interact nonlinearly. This nonlinearity is more pronounced when considering the river flow due to the tidal wave–current interaction.

The ability of a barotropic model to simulate sea level extremes of meteorological origin in the Mediterranean Sea, including those caused by explosive cyclones

Storm surges are responsible for great damage to coastal property and loss of life every year. Coastal management and adaptation practices are essential to reduce such damage. Numerical models provide a useful tool for informing these practices as they simulate sea level with high spatial resolution. Here we investigate the ability of a barotropic version of the HAMSOM model to simulate sea level extremes of meteorological origin in the Mediterranean Sea, including those caused by explosive cyclones. For this purpose, the output of the model is compared to hourly sea level observations from six tide gauge records (Valencia, Barcelona, Marseille, Civitavecchia, Trieste, and Antalya). It is found that the model underestimates the positive extremes significantly at all stations, in some cases by up to 65%. At Trieste, the model can also sometimes overestimate the extremes significantly. The differences between the model and the residuals are not constant for extremes of a given height, which limits the applicability of the numerical model for storm surge forecasting because calibration is difficult. The 50 and 10 year return levels are reasonably well captured by the model at all stations except Barcelona and Marseille, where they are underestimated by over 30%. The number of exceedances of the 99.9th and 99.95% percentiles over a period of 25 years is severely underestimated by the model at all stations. The skill of the model for predicting the timing and value of the storm surges seems to be higher for the events associated with explosive cyclones at all stations.

NUMERICAL SIMULATION OF CYCLONIC STORM SURGES OVER THE BAY OF BENGAL USING A METEOROLOGY-WAVE-SURGE-TIDE COUPLED MODEL

The purpose of this study was to evaluate the performance of an integrated meteorology and storm surge model for both the hind casting and prediction of future climate change intensified cyclones over the Bay of Bengal. This meteorology based storm surge model was developed and applied by integrating a mesoscale WRF model with the wave model SWAN and coastal ocean model FVCOM. The coupled model could capture the actual phenomena of historical cyclone Nargis, which made landfall in Myanmar in 2008, accurately and reproduce the total water level rise due to this event. The model was then used to also simulate future cyclones over the Bay of Bengal taking into account climate change by the year 2100.

BASIC STUDY ON ESTIMATION METHOD OF RETURN PERIOD AND VARIATION RANGE OF SEVERE STORM SURGE EVENT

Probability risk assessment of storm surge is difficult because the number of historical data of tropical cyclone is not enough for region. Most hazard maps for storm surge were designed based on the assumption that intense tropical cyclone approached in target area. However, its return period and variation range of storm surge have not been considered carefully so much. In this study, we examined them by using stochastic tropical cyclone model and physical storm surge model. Target area was Yatsushiro bay in west Kyshu Island in Japan. From physical storm surge height caused by 300 causes, we decided the severe storm surge scenario and the variation range of maximum storm surge height caused by change of translation speed and radius of tropical cyclone. Finally, by using stochastic tropical cyclone model, the return period of severe storm surge event was estimated about 370 year.

Modeling Flood Inundation Induced by River Flow and Storm Surges over a River Basin

Low-lying coastal regions and their populations are at risk during storm surge events and high freshwater discharges from upriver. An integrated storm surge and flood inundation modeling system was used to simulate storm surge and inundation in the Tsengwen River basin and the adjacent coastal area in southern Taiwan. A three-dimensional hydrodynamic model with an unstructured grid was used, which was driven by the tidal elevation at the open boundaries and freshwater discharge at the upriver boundary. The model was validated against the observed water levels for three typhoon events. The simulation results for the model were in reasonable agreement with the observational data. The model was then applied to investigate the effects of a storm surge, freshwater discharge, and a storm surge combined with freshwater discharge during an extreme typhoon event. The super Typhoon Haiyan (2013) was artificially shifted to hit Taiwan: the modeling results showed that the inundation area and depth would cause severe overbank flow and coastal flooding for a 200 year return period flow. A high-resolution grid model is essential for the accurate simulation of storm surges and inundation.

Atmospheric storm surge modeling methodology along the French (Atlantic and English Channel) coast

Storm surge modeling and forecast are the key issues for coastal risk early warning systems. As a general objective, this study aims at improving high-frequency storm surge variations modeling within the PREVIMER system (www.previmer.org), along the French Atlantic and English Channel coasts. The paper focuses on (1) sea surface drag parameterization and (2) uncertainties induced by the meteorological data quality. The modeling is based on the shallow-water version of the model for applications at regional scale (MARS), with a 2-km spatial resolution. The model computes together tide and surge, allowing properly taking into account tide-surge interactions. To select the most appropriate parameterization for the study area, a sensitivity analysis on sea surface drag parameterizations is done, based on comparisons of modeled storm surges (extracted with a tidal component analysis) with four tidal gauges, during four storm events, and over about 7.5 years, where the observed water level is processed in the same way as the modeling results. The tested drag parameterizations are a constant one, as reported by Moon et al. (J Atmos Sci 61: 2321–2333, 2007), Makin (Bound-Layer Meteorol 115: 169–176, 2005), and Charnock (J Roy Meteor Soc 81: 639–640, 1955). Charnock’s parameterization, either constant with high value (0.022) or relying on a full statistical description of the sea state, enables to improve storm surges forecast with peak errors 10 cm smaller than those computed with the other drag coefficient formulations. The impact of the meteorological forcing quality is evaluated over January 2012 from the comparison between surges modeled with different meteorological data (ARPEGE, ARPEGE High Resolution and AROME) and observations. For event time scale, storm surge computation is highly improved with ARPEGE High Resolution data. For month time scale, statistics of model accuracy are less sensitive to the choice of meteorological forcing. As a conclusion, the Charnock’s parameterization is advised to model storm surges on the French Atlantic and English Channel coasts, whereas the quality requirements regarding meteorological inputs depend on the time scale of interest. Within the PREVIMER system, aiming at forecasting events, ARPEGE High Resolution data are used.

How frequent is storm-induced flooding in the central part of the Bay of Biscay?

This study analyzes historical archives to produce a database of storm-induced coastal flooding in the French central part of the Bay of Biscay since 1500AD. From this new database, 46 coastal floods have been reported for the last 500years (1 event every 11yr on average), which demonstrates the high vulnerability of this region to coastal flooding. The limitations of historical archives prevent concluding to a change in storminess over the period. The six largest coastal floods that occurred since 1900 are further investigated because numerous informations are available in terms of meteorological conditions as well as maximum water levels reached. Associated storm surges are also modeled using a simplified methodology, relying on a fully coupled wave and circulation modeling system directly forced by the available meteorological data. The analysis of modeling results and historical archives reveals firstly that several meteo-oceanic settings can lead to extensive coastal flooding in the studied area. The analyzed events allow distinguishing three main settings: (1) a small storm surge associated with the highest astronomical tidal levels, (2) a large storm surge, induced either by extreme winds or a particular sea-state and associated with high astronomical tidal levels and, (3) a large storm surge enhanced by extreme wave conditions. Second, maximum water levels reached during these 6 coastal floods were shown to be higher than the 100years return period water level estimated in several recently published studies. This inconstancy can be explained mainly by the lack of extreme water level records in tide gauge datasets used in these previous studies. To a slightest degree, this study questions the validity of classical statistical approaches when analyzing extreme water levels data resulting from contrasting meteo-oceanic settings. It is concluded that historical archives combined with storm surge modeling could be a valuable approach to better estimate the return period of extreme sea levels and improve the understanding on the vulnerability of mixed-energy coastal environments such as the study area.

Informing conservation planning using future sea-level rise and storm surge modeling impact scenarios in the Northern Gulf of Mexico

Coastal communities across the Gulf of Mexico are increasingly vulnerable to coastal hazards, including sea level rise. The Gulf of Mexico contains 20 000 km² of land below 1.5 m in elevation and is one of the most vulnerable regions to sea level rise in the continental U.S. Wetlands are among the Gulf of Mexico's most economically and ecologically important habitats that comprise thirty-one percent (28 372 mi²) of land within the U.S. Gulf coastal watershed. These increasing hazards threaten not only the human-built infrastructure and coastal communities, but also natural habitats and ecosystems. Through a participatory stakeholder process the project team and regional stakeholders identified ongoing and future conservation planning efforts that were best suited to be informed by sea-level rise and storm surge projections, socioeconomic indicators, and marsh migration scenarios. This study estimates the potential impacts of SLR and storm surge to human communities and natural habitats, with emphasis on coastal marshlands, in both the Galveston Bay region of Texas and the Choctawhatchee and Saint Andrew Bay region of Florida. Project results include A) marsh change and viability analysis, B) community risk analysis, C) community resilience analysis; and D) long-term marsh management analysis. Our study suggests that sea-level rise impacts should be incorporated into ongoing conservation planning and management activities in order to allow decision makers to more easily develop adaptation strategies that foster coastal resilience in the face of a changing climate.

Local amplification of storm surge by Super Typhoon Haiyan in Leyte Gulf.

Typhoon Haiyan, which struck the Philippines in November 2013, was an extremely intense tropical cyclone that had a catastrophic impact. The minimum central pressure of Typhoon Haiyan was 895 hPa, making it the strongest typhoon to make landfall on a major island in the western North Pacific Ocean. The characteristics of Typhoon Haiyan and its related storm surge are estimated by numerical experiments using numerical weather prediction models and a storm surge model. Based on the analysis of best hindcast results, the storm surge level was 5–6 m and local amplification of water surface elevation due to seiche was found to be significant inside Leyte Gulf. The numerical experiments show the coherent structure of the storm surge profile due to the specific bathymetry of Leyte Gulf and the Philippines Trench as a major contributor to the disaster in Tacloban. The numerical results also indicated the sensitivity of storm surge forecast.

Numerical models sea surface wind compared to scatterometer observations for a single Bora event in the Adriatic Sea

Abstract. We compare the sea surface wind fields forecasted by a Global Circulation Model (GCM) and three Limited Area Models (LAMs) in an operational-like set-up, with the wind remotely sensed by the NASA QuikSCAT scatterometer. The comparison is performed for a single case of Bora wind in the Adriatic Sea, with the purpose to understand the ability of the model forecasts in reproducing the mesoscale features captured by the scatterometer, and to investigate on the suitability of LAM and GCM forecasts as possible forcing in storm surge models (SSMs). The performance is evaluated by means of statistical parameters regarding wind speed and direction showing that, at least in terms of classical statistical parameters, the GCM offer the most advantageous choice in terms of cost/benefit.

Mapping joint hurricane wind and surge hazards for Charleston, South Carolina

Combined effects of hurricane wind and surge can pose significant threats to coastal cities. Although current design codes consider the joint occurrence of wind and surge, information on site-specific joint distributions of hurricane wind and surge along the US Coast is still sparse and limited. In this study, joint hazard maps for combined hurricane wind and surge for Charleston, South Carolina (SC), were developed. A stochastic Markov chain hurricane simulation program was utilized to generate 50,000 years of full-track hurricane events. The surface wind speeds and surge heights from individual hurricanes were computed using the Georgiou's wind field model and the Sea, Lake and Overland Surges from Hurricanes (SLOSH) model, respectively. To validate the accuracy of the SLOSH model, the simulated surge levels were compared to the surge levels calculated by another state-of-the-art storm surge model, ADCIRC (Advanced Circulation), and the actual observed water elevations from historical hurricane events. Good agreements were found between the simulated and observed water elevations. The model surface wind speeds were also compared with the design wind speeds in ASCE 7-10 and were found to agree well with the design values. Using the peak wind speeds and maximum surge heights, the joint hazard surfaces and the joint hazard maps for Charleston, SC, were developed. As part of this study, an interactive computer program, which can be used to obtain the joint wind speed and surge height distributions for any location in terms of latitude and longitude in Charleston area, was created. These joint hazard surfaces and hazard maps can be used in a multi-hazard design or risk assessment framework to consider the combined effects of hurricane wind and surge. Language: en

Research of the Influential Factors on the Simulation of Storm Surge in the Bohai Sea

A hindcast of typical extratropical storm surge occurring in the Bohai Sea in Oct. 2003 is performed using a three-dimensional storm surge model system based on Finite-Volume Coastal Ocean Model (FVCOM). The surface winds are obtained from the WRF data set. Some preliminary sensitivity studies of the influential factors affecting the storm surge simulation in the Bohai Sea are conducted with the high revolution numerical model of storm surge. The factors of tide-surge interaction, the wind stress, the water depth, the bottom drag coefficient and the critical depth in the model are studied. After considering the tide-wind interaction and the severe wind, the most important influential factor affecting the storm surge in the Bohai Sea is the bottom drag coefficient. These sensitivity studies indicate that the storm surge simulations depend critically on the parameterizations. Hence additional experimental guidance is required on the bottom drag coefficient. This study is useful for the storm surge simulation in order to select the proper parameter to make possible a good conservation behavior of the storm surge model.

Strengthening the Resiliency of a Coastal Transportation System through Integrated Simulation of Storm Surge, Inundation, and Nonrecurrent Congestion in Northeast Florida

The Multimodal Transportation Educational Virtual Appliance (MTEVA) is an application developed within the framework of the broader Coastal Science Educational Virtual Appliance (CSEVA) to enhance coastal resiliency through the integration of coastal science and transportation congestion models for emergency situations. The first generation MTEVA enabled users to perform and visualize simulations using an integrated storm surge and inundation model (CH3D-SSMS) and transportation evacuation/return modeling system that supports contraflow in a simple synthetic domain (order of tens of intersections/roads) under tropical storm conditions. In this study, the second generation MTEVA has been advanced to apply storm surge and evacuation models to the greater Jacksonville area of Northeast Florida (order tens of thousands of transportation intersections/roads). To support solving the evacuation problem with a significantly larger transportation network, new models have been developed, including a heuristic capable of efficiently solving large-scale problems. After initial testing on several smaller stand-alone transportation networks (e.g., Anaheim, Winnipeg), the heuristic is applied to the Jacksonville area transportation network. Results presented show the heuristic produces a nearly optimal (average optimality gap <0.5%) solution in 90% less wall clock time than needed by the exact solver. The MTEVA’s new capabilities are then demonstrated through the simulation of a Hurricane Katrina-sized storm impacting the region and studying how the evacuation patterns are affected by the closing of roads due to flooding and bridges due to high winds. To ensure residents are able to leave the area, evacuations are shown to need to have begun at least 36 h prior to landfall. Additionally it was shown that large numbers of residents would be left behind if evacuation does not begin within 18 h of landfall and ~97% would not escape if evacuation did not begin until landfall, when areas of the coast that are the most prone to flooding are already cut off from the “safe” nodes of the transportation network.

The Storm Surge and Sub-Grid Inundation Modeling in New York City during Hurricane Sandy

Hurricane Sandy inflicted heavy damage in New York City and the New Jersey coast as the second costliest storm in history. A large-scale, unstructured grid storm tide model, Semi-implicit Eulerian Lagrangian Finite Element (SELFE), was used to hindcast water level variation during Hurricane Sandy in the mid-Atlantic portion of the U.S. East Coast. The model was forced by eight tidal constituents at the model’s open boundary, 1500 km away from the coast, and the wind and pressure fields from atmospheric model Regional Atmospheric Modeling System (RAMS) provided by Weatherflow Inc. The comparisons of the modeled storm tide with the NOAA gauge stations from Montauk, NY, Long Island Sound, encompassing New York Harbor, Atlantic City, NJ, to Duck, NC, were in good agreement, with an overall root mean square error and relative error in the order of 15–20 cm and 5%–7%, respectively. Furthermore, using large-scale model outputs as the boundary conditions, a separate sub-grid model that incorporates LIDAR data for the major portion of the New York City was also set up to investigate the detailed inundation process. The model results compared favorably with USGS’ Hurricane Sandy Mapper database in terms of its timing, local inundation area, and the depth of the flooding water. The street-level inundation with water bypassing the city building was created and the maximum extent of horizontal inundation was calculated, which was within 30 m of the data-derived estimate by USGS.

Deterministic and probabilistic flood modeling for contemporary and future coastal and inland precipitation inundation

While hazard mitigation lowers hazard impacts, communities cannot mitigate all possible risks. Targeting mitigation allows agencies with limited resources to mitigate areas within a community where hazard impacts are highest. To target these areas effectively, better hazard modeling is needed to provide more accurate hazard extents to pinpoint mitigation and conduct more complete vulnerability assessments. Deterministic models are useful for developing mitigation policies based on their hazard identification and exposure outputs in vulnerability analyses, but are limited because they do not calculate risk. Probabilistic models provide more information about the range of risk allowing decision makers to target mitigation and land-use management focuses toward areas of higher risk. Deterministic models used in conjunction with probabilistic models can also be used to perform all three levels of vulnerability assessment and produce more complete hazard modeling extents, which is something not traditionally done. To explore the need for the use of probabilistic models in conjunction with deterministic modeling, research presented here creates a theoretical framework for a stochastic storm surge model using deterministic hazard extents that depict coastal hazard inundation, using Sarasota County, Florida as a case study. The deterministic hazard extents are created for use in multiscalar vulnerability assessments that simulate storm surge, inland precipitation and sea-level rise (SLR) to depict holistic coastal hazard inundation. The deterministic extents also provide higher-resolution hazard identification that can aid local decision makers targeting high-risk areas, not all exposed areas.