Storm Surge Model Research Articles

Prediction of atmospheric motion vectors around typhoons using generative adversarial network

In this study, atmospheric motion vectors (AMVs) were derived from the satellite images predicted using a generative adversarial network (GAN) and a deep multi-scale frame prediction algorithm. The GAN was trained and tested with a sequence of the satellite images of a COMS satellite infrared-window channel under the 68 tropical cyclones. The inputs of the consecutive satellite images with 15-min interval were then processed using the trained GAN model to generate satellite images in the next time steps. To further enhance the model’s predictability, particle image velocimetry based on the theory of cross-correlation schemes was employed to the GAN-generated satellite image sequence and AMVs were produced. The GAN-derived AMVs were validated with the wind fields based on the numerical weather prediction (NWP) and radiosonde observations. The comparisons showed that the GAN-derived AMVs depicted the structure of atmospheric circulations with a certain level of accuracy. Through comparison with the radiosonde observations, the root-mean-square error and the wind speed bias of the GAN-derived AMVs were comparable to, and even smaller than those of the NWP-derived wind fields. The current approach may enhance the accuracy in predicting short-term wind velocity fields, which in turn may provide more realistic inputs in storm surge modeling.

Modeling Study on the Asymmetry of Positive and Negative Storm Surges along the Southeastern Coast of China

In this paper, a three-dimensional storm surge model was developed based on the Finite Volume Community Ocean Model (FVCOM) by the hindcasts of four typhoon-induced storm surges (Chan-hom, Mireille, Herb, and Winnie). After model validation, a series of sensitivity experiments were conducted to explore the effects of key parameters in the wind and pressure field (forward speed, radius of maximum wind (RMW), inflow angle, and central pressure), typhoon path, wind intensity, and topography on the storm surge and surge asymmetry between sea level rise (positive surge) and fall (negative surge) along the southeastern coast of China (SCC). The model results show that lower central pressure and larger RMW could lead to stronger surge asymmetry. A larger inflow angle results in a stronger surge asymmetry. In addition, the path of Chan-hom is the most dangerous path type for the Zhoushan Archipelago area, and that of Winnie follows next. The model results also indicate that the non-linear interaction between wind field and pressure field tends to weaken the peak surge elevation. The effect of topography on storm surges indicates that the peak surge elevation and its occurrence time, as well as the surge asymmetry, increase with a decreasing slope along the SCC.

Adjoint-based sensitivity analysis for a numerical storm surge model

Numerical storm surge models are essential to forecasting coastal flood hazard and informing the design of coastal defences. However, such models rely on a variety of inputs, many of which carry uncertainty. An awareness and understanding of the sensitivity of model outputs with respect to those uncertain inputs is therefore essential when interpreting model results. Here, we use an unstructured-mesh numerical coastal ocean model, Thetis, and its adjoint, to perform a sensitivity analysis for a hindcast of the 5th/6th December 2013 North Sea surge event, with respect to the bottom friction coefficient, bathymetry and wind stress forcing. The results reveal spatial and temporal patterns of sensitivity, providing physical insight into the mechanisms of surge generation and propagation. For example, the sensitivity of the skew surge to the bathymetry reveals the protective effect of a sand bank off the UK east coast. The results can also be used to propagate uncertainties through the numerical model; based on estimates of model input uncertainties, we estimate that modelled skew surges carry uncertainties of around 5 cm and 15 cm due to bathymetry and bottom friction, respectively. While these uncertainties are small compared with the typical spread in an ensemble storm surge forecast due to uncertain meteorological inputs, the adjoint-derived model sensitivities can nevertheless be used to inform future model calibration and data acquisition efforts in order to reduce uncertainty. Our results demonstrate the power of adjoint methods to gain insight into a storm surge model, providing information complementary to traditional ensemble uncertainty quantification methods.

Variational data assimilation of sea surface height into a regional storm surge model: Benefits and limitations

ABSTRACT Storm surges are coastal sea-level variations caused by meteorological conditions. It is vital that they are forecasted accurately to reduce the potential for financial damage and loss of life. In this study, we investigate how effectively the variational assimilation of sparse sea level observations from tide gauges can be used for operational forecasting in the North Sea. Novel data assimilation ideas are considered and evaluated: a new shortest-path method for generating improved distance-based correlations in the presence of coastal boundaries and an adaptive error covariance model. An assimilation setup is validated by removing selections of tide gauges from the assimilation procedure for a North Sea case study. These experiments show widespread improvements in RMSE and correlations, reaching up to 16 cm and 0.7 (respectively) at some locations. Simulated forecast experiments show RMSE improvements of up to 5 cm for the first 24 h of forecasting, which is useful operationally. Beyond 24 h, improvements quickly diminish however. Using the setup based on the shortest path algorithm shows little difference when compared to a simpler Euclidean method at most locations. Analysis of this event shows that improvements due to data assimilation are bounded and relatively short lived.

Effects of coastal reclamation on the storm surge in the Bohai Bay

In recent years, the Bohai Bay has experienced frequent reclamation activities and significant changes in the coastline with the rapid development of economy. Coastline changes will influence the propagation of tide and ocean waves, and the storm surges may get worse as well. Based on the ADCIRC storm surge model, an unstructured triangular grid model driven by tide and wind was established to simulate the storm surge in Bohai Sea. The numerical simulation of hydrodynamic environment during typhoon NO.9711 under four coastline scenarios which are 1980, 2004, 2008 and 2015 had been carried out to investigate how coastal reclamation affects storm surges. The results reveal that the storm surge level and hazard risk in the reclamation areas has increased along with the changes of the coastline.

Effects of nonlinear terms and topography in a storm surge model along the southeastern coast of China: a case study of Typhoon Chan-hom

Based on Finite Volume Coastal Ocean Model (FVCOM), this study constructed a numerical model covering the Bohai Sea, Yellow Sea, and East China Sea. National Centers for Environmental Prediction’s Climate Forecast System Reanalysis (NCEP-CFSR) data were used to drive the model to simulate a large storm surge generated by Typhoon Chan-hom. The model was validated by multiple in situ observations of water levels taken at tidal gauge stations. The effects of the nonlinear terms and topography on the modeling of storm surges were then studied. First, the tide–surge interaction during the storm surge process was analyzed. The results show that the tide–surge interaction can suppress the storm surge at the climax of the astronomical tide and benefit the growth of the storm surge at the ebb of the astronomical tide. The tidal constituents M2, S2 and K1 were added to analyze the influences of the amplitudes and periods of tides on the nonlinear reaction. The results indicate that the nonlinear effect will be enhanced by an increased tidal height; additionally, the nonlinear interaction of semidiurnal tides is more significant than that of diurnal tides. The semidiurnal fluctuation that appears near the peak-value time is also attributed to the tide–surge interaction. Moreover, the tide–surge interaction can be influenced by the water depth and position of the area of interest. According to the numerical results, topography has a certain impact on the storm surge: The peak value of the storm surge will decrease with increasing slope. The existence of the Ryukyu Islands reduces the area influenced by the storm surge on the southeast coast of China but expands the high-value storm surge area.

Impact of Management Regime and Regime Change on Gravel Barrier Response to a Major Storm Surge

Gravel barriers represent physiographic, hydrographic, sedimentary, and ecological boundaries between inshore and open marine offshore environments, where they provide numerous important functions. The morphosedimentary features of gravel barriers (e.g., steep, energy reflective form) have led to their characterization as effective coastal defense features during extreme hydrodynamic conditions. Consequently, gravel barriers have often been intensively managed to enhance coastal defense functions. The Blakeney Point Barrier System (BPBS), U.K., is one such example, which offers the opportunity to investigate the impact of alternative management regimes under extreme hydrodynamic conditions. The BPBS was actively re-profiled along its eastern section from the 1950s to the winter of 2005, whilst undergoing no active intervention along its western section. Combining an analysis of remotely sensed elevation datasets with numerical storm surge modeling, this paper finds that interventionist management introduces systemic differences in barrier morphological characteristics. Overly steepened barrier sections experience greater wave run-up extents during storm surge conditions, leading to more extreme morphological changes and landward barrier retreat. Furthermore, while high, steep barriers can be highly effective at preventing landward flooding, in cases where overwashing does occur, the resultant landward overtopping volume is typically higher than would be the case for a relatively lower crested barrier with a lower angled seaward slope. There is a growing preference within coastal risk management for less interventionist management regimes, incorporating natural processes. However, restoring natural processes does not immediately or inevitably result in a reduction in coastal risk. This paper contributes practical insights regarding the time taken for a previously managed barrier to relax to a more natural state, intermediary morphological states, and associated landward water flows during extreme events, all of which should be considered if gravel barriers are to be usefully integrated into broader risk management strategies.

Evaluation of parametric wind models for more accurate modeling of storm surge: a case study of Hurricane Michael

Storm surge induced by hurricane is a major threat to the Gulf Coasts of the United States. A numerical modeling study was conducted to simulate the storm surge during Hurricane Michael, a category 5 hurricane that landed on the Florida Panhandle in 2018. A high-resolution model mesh was used in the ADCIRC hydrodynamic model to simulate storm surge and tides during the hurricane. Two parametric wind models, Holland 1980 model and Holland 2010 model, have been evaluated for their effects on the accuracy of storm surge modeling by comparing simulated and observed maximum water levels along the coast. The wind model parameters are determined by observed hurricane wind and pressure data. Results indicate that both Holland 1980 and Holland 2010 wind models produce reasonable accuracy in predicting maximum water level in Mexico Beach, with errors between 1 and 3.7%. Comparing to the observed peak water level of 4.74 m in Mexico Beach, Holland 1980 wind model with radius of 64-knot wind speed for parameter estimation results in the lowest error of 1%. For a given wind model, the wind profiles are also affected by the wind data used for parameter estimation. Away from hurricane eye wall, using radius of 64-knot wind speed for parameter estimation generally produces weaker wind than those using radius of 34-knot wind speed for parameter estimation. Comparing model simulated storm tides with 17 water marks observed along the coast, Holland 2010 wind model using radius of 34-knot wind speed for parameter estimation leads to the minimum mean absolute error. The results will provide a good reference for researchers to improve storm surge modeling. The validated model can be used to support coastal hazard mitigation planning.

Tropical cyclone risk mapping for a coastal city using geospatial techniques

Tropical cyclone associated storm surges and their disastrous influences are becoming a major concern amongst the worldwide coastal community. The detailed risk modelling study seems an urgent need to support the storm surge mitigation actions. Using a Geographic Information System (GIS) based risk model, this study attempted to obtain both present and future storm surge wave heights in the Cox’s Bazar Sadar Upazilla in Bangladesh. Linear storm surge model setup was done for the different return periods includes 5, 10, 20, 50, and 100 years. Also, to assess climate change effects, a 0.34 m sea-level rise in 2050 was tested using the regional scale surge models. The simulated storm surge model provided a time series dataset for the risk model and obtained risk maps comprised of the relationship among risk zone and the return periods. With the present inundation depth trend, the acquired risk maps of 50 and 100 year return period showed that 10.13% and 36.4% of the study area belongs to very high-risk zone respectively. Conversely, for future inundation depth conditions 30.83% and 49.9% of the study area would be within a very high-risk zone in 50 and 100 year return period respectively. This is envisaged that a detailed historical inundation dataset could enrich the adopted approach considering both present and future storm surge risk modelling for the Decision Support System (DSS). Also, this approach might be adopted for other identical coastal environments to aid mitigation programs and strategies.

Effects of sea level rise on storm surges in the south Yellow Sea: A case study of Typhoon Muifa (2011)

Changes in sea levels due to climate change are expected to alter storm surge intensities worldwide, disproportionately effecting coastal communities. In this study, we explored the impacts of future sea level rise (SLR) on storm surges within various numerical frameworks. The relative mean sea level rise (RMSLR) scenario for a period of 100-yr was applied using satellite altimetry of sea surface height and subsequently adjusted for the influence of glacial isostatic adjustment (GIA) using the ICE-6G/VM5a model. For comparison purpose, two additional RMSLR distributions under Representative Concentration Pathway (RCP) scenarios were also evaluated from climate system model (CSM) ensembles and GIA. These spatially variable RMSLR scenarios were then incorporated into a high-resolution storm surge model using elevated present-day water depths to solve for coupled tide–surge–wave processes. The performance of the model was validated using in situ measurements of astronomical tides, storm tides and ocean waves. Due to the significant variability in the spatial distribution of future relative mean sea level trends in the Yellow Sea, the simplified, uniform RMSLR scenario was found to alter the responses of storm surges. The amplification or attenuation of surge heights was not solely affected by the magnitude of sea level change itself, but also modulated by changing tidal ranges and waves due to SLR. The amplification effects of tidal ranges and nonlinearities within radial sand ridges in the south Yellow Sea tended to be underestimated under the uniform scenario, suggesting that the impacts of SLR on storm surges in this region may represent underestimates.

Numerical analysis on the effect of wave boundary condition in storm wave and surge modeling for a tropical cyclonic condition

In a swell dominated region like the Northern Indian Ocean basin, the effect of pre-existing waves will play a significant role in the non-linear wave-wave interactions during cyclonic conditions, where the sea is dominated with high-frequency waves. Hence, to include such complex phenomenon into the numerical model, the present study aims at forcing a pre-run two-dimensional wave spectral output from an unstructured global coarser domain as a wave boundary condition to a finer regional domain. The storm wave and surge simulations were performed for the duration of cyclone Phailin (2013). A coupled (ADCIRC + SWAN) model was used for both, generating the spectrum, as well as the estimation of surge and wave attributes. Additionally, both storm wave and surge were simulated without considering the nested wave boundary condition, followed by the comparison and analyses of the modeled results with the field data. The investigation showed that the inclusion of wave boundary condition in the model resulted in closer agreement of the simulated wave parameters with the observed field data. The residual surge results also correlated well with the in-situ measurements, while the spatial representation of maximum water levels essentially revealed the spread of surge and its associated inundation.

BOUSSINESQ MODELING OF COMBINED STORM SURGE AND WAVES OVER WETLANDS FORCED BY WIND

Coastal wetlands protect the shoreline and infrastructure by attenuating wind waves and reducing storm surge. It is of importance to accurately quantify the flood protection provided by vegetation. Existing numerical models for hurricane waves and storm surge are based on the phase-averaged wave action balance equation and the nonlinear shallow water equations, respectively, with the wind forcing and vegetal drag as the free surface and bottom boundary conditions. To consider the interaction of waves and surge, the phase-averaged short wave and long wave (storm surge) models can be coupled in a staggered fashion. If the time step of the wave model and storm surge model are 30 minutes and 1 s, respectively, both models would exchange information every 30 minutes. There is no iteration between the wave and surge models at each coupling interval. An alternative to this state-of-the-practice of hurricane wave and storm surge modeling is to simulate the combined wave and surge motion driven by wind and attenuated by wetland vegetation using a phase-resolving Boussinesq model. The objective of this study is threefold: 1) to demonstrate the capability of modeling wave growth by wind, wave reduction by vegetation, and the total water level (wave setup, wind setup and wave runup) using the extended FUNWAVE-TVD model; 2) to analyze the energy balance of the combined wave and surge motion; 3) to examine the momentum balance with an emphasis on the vegetal drag owing to the combined wave orbital velocity and wind-driven current velocity.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/-o_kx4hPvC8

MTrack: Improved Center Fix of Tropical Cyclones from SMAP Wind Observations

AbstractMTrack is an automated algorithm that determines the center location (latitude and longitude) of a tropical cyclone from a scalar wind field derived from satellite observations. Accurate storm centers are useful for operational forecasting of tropical cyclones and for their reanalysis (e.g., research on storm surge modeling). Currently, storm center fixes have significantly larger errors for weak, disorganized storms. The MTrack algorithm presented here improves storm centers in some of those cases. It is also automated and, therefore, less subjective than manual fixes made by forecasters. The MTrack algorithm, which was originally designed to work with CYGNSS wind speed measurements, is applied to SMAP winds for the first time. The average difference between MTrack and Best Track storm center locations is 21, 36, and 46 km for major hurricanes, category 1–2 hurricanes, and tropical storms, respectively. MTrack is shown to operate successfully when a storm is only partially sampled by the observing satellite and when the eye of the storm is not resolved.

Projected Changes in Compound Flood Hazard From Riverine and Coastal Floods in Northwestern Europe

AbstractCompound flooding in coastal regions, that is, the simultaneous or successive occurrence of high sea levels and high river flows, is expected to increase in a warmer world. To date, however, there is no robust evidence on projected changes in compound flooding for northwestern Europe. We combine projected storm surges and river floods with probabilistic, localized relative sea‐level rise (SLR) scenarios to assess the future compound flood hazard over northwestern coastal Europe in the high (RCP8.5) emission scenario. We use high‐resolution, dynamically downscaled regional climate models (RCM) to drive a storm surge model and a hydrological model, and analyze the joint occurrence of high coastal water levels and associated river peaks in a multivariate copula‐based approach. The RCM‐forced multimodel mean reasonably represents the observed spatial pattern of the dependence strength between annual maxima surge and peak river discharge, although substantial discrepancies exist between observed and simulated dependence strength. All models overestimate the dependence strength, possibly due to limitations in model parameterizations. This bias affects compound flood hazard estimates and requires further investigation. While our results suggest decreasing compound flood hazard over the majority of sites by 2050s (2040–2069) compared to the reference period (1985–2005), an increase in projected compound flood hazard is limited to around 34% of the sites. Further, we show the substantial role of SLR, a driver of compound floods, which has frequently been neglected. Our findings highlight the need to be aware of the limitations of the current generation of Earth system models in simulating coastal compound floods.

Population Exposure to Amphan-Scale Cyclones Under Future Climates

Background: Climate change impacts are felt disproportionately in developing countries, and in particular Southern Asia experiences the most damaging hydrometeorological events in the world, with loss of life from past cyclones in the hundreds of thousands. Despite this, the Bay of Bengal cyclone basin receives far less research attention than many of the others around the world. Here, we study the historical and future impacts of Super Cyclone Amphan, which made landfall in May 2020, bringing storm surges of 2-4 meters to coastlines of India and Bangladesh. Methods: In this modelling study, we combine projections of sea level rise from the Coupled Model Intercomparison Projection, phase 6 (CMIP6), with estimates of storm surge using a dynamic storm surge model. Sampling the spectrum of possible sea level rises, we consider a low, medium and high scenario, based on projections in 2100. We then feed these into a flood inundation model to simulate storm surge-induced flooding, had Cyclone Amphan occurred in these future worlds. Finally, we consider the change in future population growth and urbanisation, thereby calculating the change in population exposure to these future flooding events. Our approach is that of the extreme event attribution community, but projecting into the future rather than interrogating the past. Findings: We find that in 2100, the local sea level rise in the Bay of Bengal during the pre-monsoon cyclone season is between 0.32-0.84 m, depending on which emissions scenario is followed. If a Cyclone Amphan-scale storm surge occurred on top of that sea level rise, the future population of both India and Bangladesh will be more exposed, with India showing >200% increased exposure to extreme (>3 m) and moderate (>1 m) flooding under a high emissions scenario, and Bangladesh showing ~60-80% increased exposure to the same scenarios. The majority of this change in both countries comes from sea level rise rather than population changes, and in Bangladesh the future population change contributes negatively to the change in exposure, as more citizens migrate further inshore. However, if we follow an emissions scenario consistent with meeting the upper Paris Agreement climate goal, we project very little change in exposure. Interpretation: There is an urgent need to reduce carbon emissions to net zero, to prevent the negative impacts of climate change. By far the majority of cyclone research has been undertaken for countries such as America and Japan, with less resilient countries such as those in South Asia, which are more sensitive to changes in climate, seeing far less attention. With Cyclone Amphan occurring at the height of the COVID-19 crisis, we highlight how the risk was compounded and recommend that future climate risk assessments explicitly account for these potential non-linearities. Funding Statement: The main funding is from the Natural Environment Research Council.Declaration of Interests: The authors declare no competing interests.

Effect of landfall location and coastal topography on surge response in the Northern Bay of Bengal

Storm surges caused by frequent cyclone events have posed severe threats to the inhabitants of the northern Bay of Bengal. In this study, a high-resolution, two-dimensional, hydrodynamic storm surge model was developed using the Semi-implicit Cross-scale Hydroscience Integrated System Model (SCHISM) to investigate storm surges in the Bay of Bengal. After validation, the storm surge of the study area was simulated for 11 idealized cyclone cases, the tracks of which were approximately perpendicular to the head of Bay of Bengal when landing at high-tide and low-tide time, respectively. The simulation results show that when landing at the high-tide time, the cyclone produced a peak surge height of about 85% of that when landing at the low-tide time, on average. It is also shown that when cyclone landed during the low-tide time, there was a delay of about 90-130 min for the arrival time of peak surge at the right side of the landfall position, compared with that landed during the high-tide time. Finally, we found that, for the area of the head of the bay, the surge response in the middle-eastern part was weak than that in other parts. This study demonstrates the importance of including the tide-surge interaction in the simulation of storm surge and provides the difference of the surge responses between different shore sections of the study area, which may be useful for the prediction and mitigation of the storm surge disaster.

Long-Lead-Time Prediction of Storm Surge Using Artificial Neural Networks and Effective Typhoon Parameters: Revisit and Deeper Insight

Storm surge induced by severe typhoons has caused many catastrophic tragedies to coastal communities over past decades. Accurate and efficient prediction/assessment of storm surge is still an important task in order to achieve coastal disaster mitigation especially under the influence of climate change. This study revisits storm surge predictions using artificial neural networks (ANN) and effective typhoon parameters. Recent progress of storm surge modeling and some remaining unresolved issues are reviewed. In this paper, we chose the northeastern region of Taiwan as the study area, where the largest storm surge record (over 1.8 m) has been observed. To develop the ANN-based storm surge model for various lead-times (from 1 to 12 h), typhoon parameters are carefully examined and selected by analogy with the physical modeling approach. A knowledge extraction method (KEM) with backward tracking and forward exploration procedures is also proposed to analyze the roles of hidden neurons and typhoon parameters in storm surge prediction, as well as to reveal the abundant, useful information covered in the fully-trained artificial brain. Finally, the capability of ANN model for long-lead-time predictions and influences in controlling parameters are investigated. Overall, excellent agreement with observations (i.e., the coefficient of efficiency CE > 0.95 for training and CE > 0.90 for validation) is achieved in one-hour-ahead prediction. When the typhoon affects coastal waters, contributions of wind speed, central pressure deficit, and relative angle are clarified via influential hidden neurons. A general pattern of maximum storm surge under various scenarios is also obtained. Moreover, satisfactory accuracy is successfully extended to a much longer lead time (i.e., CE > 0.85 for training and CE > 0.75 for validation in 12-h-ahead prediction). Possible reasons for further accuracy improvement compared to earlier works are addressed.

Quantitative assessment of inundation risks from physical contributors associated with future storm surges: a case study of Typhoon Maemi (2003)

Future storm-induced inundation risks were assessed by performing storm surge modeling based on Typhoon Maemi (2003) under the generic climate change scenarios proposed by IPCC AR5. The three physical factors governing the projected aggravation of inundation damage in a coastal basin (i.e., sea-level rise (SLR), direct runoff (DR) and tropical cyclones (TCs)) were defined and considered in the modeling both individually and in combination. With the application of a coupled hydrodynamic–hydrologic model, the inundation extent during the storm event under both current and year 2100 climate conditions was evaluated, and the impact of each factor on the inundation risk was identified. The intercomparison among the results revealed that SLR was the most influential single flooding driver aggravating the future inundation risk, and TC intensification was two-thirds as influential as SLR. However, DR was predicted to make a nearly negligible contribution and to have a minimal impact despite its significant projected increase in the future. Apart from the contributions of these three factors to aggravating the inundation level, the ways in which they affected the inundation risk were quite distinct. Additionally, the result considering both SLR and TC intensification demonstrated that nonlinear interactions between these factors can occur and further amplify the inundation damage. Finally, it was revealed that, depending on the level of the climate change projection, future storms with intensified rainfall and TC properties are likely to cause the maximum projected inundation damage in the study area to increase by up to 28.7% in inundation extent and by 236.6% in inundation volume relative to the current conditions without altering the spatial pattern of the inundation depth distribution.

Integrated modelling of sea-state forecasts for safe navigation and operational management in ports: Application in the Mediterranean Sea

In this paper we present recent evolvements of three robust numerical models for the simulation of the evolution of wave fields and hydrodynamic circulation in gulfs and coastal areas with large harbours and significant urban port facilities. The models are integrated into a single software suite for the development of a decision support tool to provide reliable forecasts of sea states prevailing at selected important ports worldwide. The application of the integrated modelling platform is designed to support approaching procedures of vessels to ports and it is based on co-operating, high-resolution, hydrodynamic (ocean and wave) models that derive input data and boundary conditions from global scale or regional, open sea and weather forecasts. The implementation of short-term forecasts for sea conditions includes the development, validation, coupling, and operational application of: i) the High Resolution Storm Surge (HiReSS) model for sea level variations; ii) the 3rd generation spectral wave model called TELEMAC-based Operational Model Addressing Wave Action Computation (TOMAWAC) for irregular wave propagation in offshore and coastal areas; and iii) a high resolution phase-resolving wave model (WAVE-L) for port basins, based on the hyperbolic mild-slope equations. This innovative product, designed for port-related end-users, will improve the navigation safety at ports, optimize the berth occupancy, support the port pilotage operations, mooring and towage procedures, and may facilitate the port layout upgrade or design. Hereby, pilot forecast implementations are presented concerning the Mediterranean Sea and eight selected harbours in it.

A Rapid Forecasting and Mapping System of Storm Surge and Coastal Flooding

AbstractA prototype of an efficient and accurate rapid forecasting and mapping system (RFMS) of storm surge is presented. Given a storm advisory from the National Hurricane Center, the RFMS can generate a coastal inundation map on a high-resolution grid in 1 min (reference system Intel Core i7–3770K). The foundation of the RFMS is a storm surge database consisting of high-resolution simulations of 490 optimal storms generated by a robust storm surge modeling system, Curvilinear-Grid Hydrodynamics in 3D (CH3D-SSMS). The RFMS uses an efficient quick kriging interpolation scheme to interpolate the surge response from the storm surge database, which considers tens of thousands of combinations of five landfall parameters of storms: central pressure deficit, radius to maximum wind, forward speed, heading direction, and landfall location. The RFMS is applied to southwest Florida using data from Hurricane Charley in 2004 and Hurricane Irma in 2017, and to the Florida Panhandle using data from Hurricane Michael in 2018 and validated with observed high water mark data. The RFMS results agree well with observation and direct simulation of the high-resolution CH3D-SSMS. The RFMS can be used for real-time forecasting during a hurricane or “what-if” scenarios for mitigation planning and preparedness training, or to produce a probabilistic flood map. The RFMS can provide more accurate surge prediction with uncertainties if NHC can provide more accurate storm forecasts in the future. By incorporating storms for future climate and sea level rise, the RFMS could be used to generate future flood maps for coastal resilience and adaptation planning.