Advances in surrogate modeling for storm surge prediction: storm selection and addressing characteristics related to climate change

This paper establishes various advancements for the application of surrogate modeling techniques for storm surge prediction utilizing an existing database of high-fidelity, synthetic storms (tropical cyclones). Kriging, also known as Gaussian process regression, is specifically chosen as the surrogate model in this study. Emphasis is first placed on the storm selection for developing the database of synthetic storms. An adaptive, sequential selection is examined here that iteratively identifies the storm (or multiple storms) that is expected to provide the greatest enhancement of the prediction accuracy when that storm is added into the already available database. Appropriate error statistics are discussed for assessing convergence of this iterative selection, and its performance is compared to the joint probability method with optimal sampling, utilizing the required number of synthetic storms to achieve the same level of accuracy as comparison metric. The impact on risk estimation is also examined. The discussion then moves to adjustments of the surrogate modeling framework to support two implementation issues that might become more relevant due to climate change considerations: future storm intensification and sea level rise (SLR). For storm intensification, the use of the surrogate model for prediction extrapolation is examined. Tuning of the surrogate model characteristics using cross-validation techniques and modification of the tuning to prioritize storms with specific characteristics are proposed, whereas an augmentation of the database with new/additional storms is also considered. With respect to SLR, the recently developed database for the US Army Corps of Engineers’ North Atlantic Comprehensive Coastal Study is exploited to demonstrate how surrogate modeling can support predictions that include SLR considerations.     

Implementation/optimization of moving least squares response surfaces for approximation of hurricane/storm surge and wave responses

One of the important recent advances in the field of hurricane/storm modelling has been the development of high-fidelity numerical simulation models for reliable and accurate prediction of wave and surge responses. The computational cost associated with these models has simultaneously created an incentive for researchers to investigate surrogate modelling (i.e. metamodeling) and interpolation/regression methodologies to efficiently approximate hurricane/storm responses exploiting existing databases of high-fidelity simulations. Moving least squares (MLS) response surfaces were recently proposed as such an approximation methodology, providing the ability to efficiently describe different responses of interest (such as surge and wave heights) in a large coastal region that may involve thousands of points for which the hurricane impact needs to be estimated. This paper discusses further implementation details and focuses on optimization characteristics of this surrogate modelling approach. The approximation of different response characteristics is considered, and special attention is given to predicting the storm surge for inland locations, for which the possibility of the location remaining dry needs to be additionally addressed. The optimal selection of the basis functions for the response surface and of the parameters of the MLS character of the approximation is discussed in detail, and the impact of the number of high-fidelity simulations informing the surrogate model is also investigated. Different normalizations of the response as well as choices for the objective function for the optimization problem are considered, and their impact on the accuracy of the resultant (under these choices) surrogate model is examined. Details for implementation of the methodology for efficient coastal risk assessment are reviewed, and the influence in the analysis of the model prediction error introduced through the surrogate modelling is discussed. A case study is provided, utilizing a recently developed database of high-fidelity simulations for the Hawaiian Islands.     

Surrogate modeling of time-dependent metocean conditions during hurricanes

Metocean conditions during hurricanes are defined by multiple parameters (e.g., significant wave height and surge height) that vary in time with significant auto- and cross-correlation. In many cases, the nature of the variation of these characteristics in time is important to design and assess the risk to offshore structures, but a persistent problem is that measurements are sparse and time history simulations using metocean models are computationally onerous. Surrogate modeling is an appealing approach to ease the computational burden of metocean modeling; however, modeling the time-dependency of metocean conditions using surrogate models is challenging because the conditions at one time instant are dependent on not only the conditions at that instant but also on the conditions at previous time instances. In this paper, time-dependent surrogate modeling of significant wave height, peak wave period, peak wave direction, and storm surge is explored using a database of metocean conditions at an offshore site. Three types of surrogate models, including Kriging, multilayer perceptron (MLP), and recurrent neural network with gated recurrent unit (RNN-GRU), are evaluated, with two different time-dependent structures considered for the Kriging model and two training set sizes for the MLP model, resulting in a total of five models evaluated in this paper. The performance of the models is compared in terms of accuracy and sensitivity toward hyperparameters, and the MLP and RNN-GRU models are demonstrated to have extraordinary prediction performance in this context.

     

The impact of extra-tropical transitioning on storm surge and waves in catastrophe risk modelling: application to the Japanese coastline

Catastrophe risk models are used to assess and manage the economic and societal impacts of natural perils such as tropical cyclones. Large ensembles of event simulations are required to generate useful model output. For example, to estimate the risk due to wind-driven storm surge and waves in tropical cyclone risk models, computationally efficient parametric representations of the wind forcing are required to enable the generation of large ensembles. This paper presents new results on the impact of including explicit representations of extra-tropical transitioning in parametric wind models used to force storm surge and wave simulations in a catastrophe risk modelling context. Extra-tropical transitioning is particularly important in modelling risk on the Japanese coastline, as roughly 40 % of typhoons hitting the Japanese mainland are transitioning before landfall. Using both a historical and idealized track set, we compare maximum storm surge and wave footprints along the Japanese coastline for models that include, and do not include, explicit representations of extra-tropical transitioning. We find that the inclusion of extra-tropical transitioning leads to lower storm surge (10–20 %) and waves (5–15 %) on the southern Japanese coast, with significantly higher storm surge and waves along the northern coast (25–50 %). The results of this paper demonstrate that useful risk assessment of coastal flood risk in Japan must consider the extra-tropical transitioning process.     

Influence of landscape restoration and degradation on storm surge and waves in southern Louisiana

The purpose of this investigation was to examine storm surge and wave reduction benefits of different environmental restoration features (marsh restoration and barrier island changes), as well as the impact of future wetland degradation on local surge and wave conditions. Storm surge simulations of two representative hurricanes were performed using the ADCIRC storm surge model with the inclusion of radiation stress gradients from the STWAVE nearshore wave model. Coupled model simulations were made for a number of landscape configurations that involved both restored and degraded wetland features. The impact of barrier island condition on hurricane surge and waves was also evaluated. Effects of landscape features were represented by changes in elevation and frictional resistance. Restoration and degradation of marsh resulted in decreases (for restoration cases) and increases (for degradation cases) in both surge and waves. The magnitude of change was correlated with the magnitude of the horizontal extent and elevation changes in the marsh. In general, the wave change patterns are consistent with the water level changes. Deflation of the Chandeleur Islands (barrier island chain) resulted in slightly increased surge. Results suggest that coastal marsh does have surge and wave reduction potential. Results also indicate that the impact of the landscape features is amplified in areas where there are levee “pockets.” Barrier islands and coastal ridges reduce wave heights, even if in a degraded condition and thus can reduce wave energy in wetland areas, protecting them from erosion.     

Simulation of atmospheric states for a storm surge on the west coast of Korea: model comparison between MM5, WRF and COAMPS

High-quality informations on sea level pressure and sea surface wind stress are required to accurately predict storm surges over the Korean Peninsula. The storm surge on 31 March 2007 at Yeonggwang, on the western coast, was an abrupt response to mesocyclone development. In the present study, we attempted to obtain reliable surface winds and sea level pressures. Using an optimal physical parameterization for wind conditions, MM5, WRF and COAMPS were used to simulate the atmospheric states that accompanied the storm surge. The use of MM5, WRF and COAMPS simulations indicated the development of high winds in the strong pressure gradient due to an anticyclone and a mesocyclone in the southern part of the western coast. The response to this situation to the storm surge was sensitive. A low-level warm advection was examined as a possible causal mechanism for the development of a mesocyclone in the generating storm surge. The low-level warm temperature advection was simulated using the three models, but MM5 and WRF tended to underestimate the warm tongue and overestimate the wind speed. The WRF simulation was closer to the observed data than the other simulations in terms of wind speed and the intensity of the mesocyclone. It can be concluded that the magnitude of the storm surge at Yeonggwang was dependent, not only on the development of a mesocyclone but on ocean effects as well.     

Impact of wind gusts on sea surface height in storm surge modelling, application to the North Sea

Storm surge models usually do not take into account the explicit effect of wind gusts on the sea surface height. However, as the wind speed enters quadratically into the shallow water equations, short-term fluctuations around the mean value do not average out. We investigate the impact of explicitly added gustiness on storm surge forecasts in the North Sea, using the WAQUA/DCSM model. The sensitivity of the model results to gustiness is tested with Monte Carlo simulations, and these are used to derive a parametrisation of the effect of gustiness on characteristics of storm surges. With the parametrisation and input from the ECMWF model archive, we run hindcasts for a few individual cases and also the 2007–2008 winter storm season. Although the explicit inclusion of gustiness increases the surge levels, it does not help to explain, and hence reduce, the errors in the model results. Moreover, the errors made by ignoring gustiness are small compared to other errors. We conclude that, at present, there is no need to include gustiness explicitly in storm surge calculations for the North Sea.     

Hurricane Katrina storm surge delineation: implications for future storm surge forecasts and warnings

The storm surge in coastal Mississippi caused by Hurricane Katrina was unprecedented in the region. The height and geographic extent of the storm surge came as a surprise to many and exceeded pre-impact surge scenarios based on SLOSH models that were the basis for emergency preparedness and local land use decision-making. This paper explores the spatial accuracy of three interpolated storm surge surfaces derived from post-event reconnaissance data by comparing the interpolation results to a specific SLOSH run. The findings are used to suggest improvements in the calibration of existing pre-event storm surge models such as SLOSH. Finally, the paper provides some suggestions on an optimal surge forecast map that could enhance the communication of storm surge risks to the public.     

Simulation of water levels and extent of coastal inundation due to a cyclonic storm along the east coast of India

The devastation due to storm surge flooding caused by extreme wind waves generated by the cyclones is a severe apprehension along the coastal regions of India. In order to coexist with nature’s destructive forces in any vulnerable coastal areas, numerical ocean models are considered today as an essential tool to predict the sea level rise and associated inland extent of flooding that could be generated by a cyclonic storm crossing any coastal stretch. For this purpose, the advanced 2D depth-integrated (ADCIRC-2DDI) circulation model based on finite-element formulation is configured for the simulation of surges and water levels along the east coast of India. The model is integrated using wind stress forcing, representative of 1989, 1996, and 2000 cyclones, which crossed different parts of the east coast of India. Using the long-term inventory of cyclone database, synthesized tracks are deduced for vulnerable coastal districts of Tamil Nadu. Return periods are also computed for the intensity and frequency of cyclones for each coastal district. Considering the importance of Kalpakkam region, extreme water levels are computed based on a 50-year return period data, for the generation of storm surges, induced water levels, and extent of inland inundation. Based on experimental evidence, it is advocated that this region could be inundated/affected by a storm with a threshold pressure drop of 66 hpa. Also it is noticed that the horizontal extent of inland inundation ranges between 1 and 1.5 km associated with the peak surge. Another severe cyclonic storm in Tamil Nadu (November 2000 cyclone), which made landfall approximately 20 km south of Cuddalore, has been chosen to simulate surges and water levels. Two severe cyclonic storms that hit Andhra coast during 1989 and 1996, which made landfall near Kavali and Kakinada, respectively, are also considered and computed run-up heights and associated water levels. The simulations exhibit a good agreement with available observations from the different sources on storm surges and associated inundation caused by these respective storms. It is believed that this study would help the coastal authorities to develop a short- and long-term disaster management, mitigation plan, and emergency response in the event of storm surge flooding.     

A modeling study of coastal inundation induced by storm surge,sea-level rise,and subsidence in the Gulf of Mexico

The northern coasts of the Gulf of Mexico (GoM) are highly vulnerable to the direct threats of climate change, such as hurricane-induced storm surge, and such risks are exacerbated by land subsidence and global sea-level rise. This paper presents an application of a coastal storm surge model to study the coastal inundation process induced by tide and storm surge, and its response to the effects of land subsidence and sea-level rise in the northern Gulf coast. The unstructured-grid finite-volume coastal ocean model was used to simulate tides and hurricane-induced storm surges in the GoM. Simulated distributions of co-amplitude and co-phase lines for semi-diurnal and diurnal tides are in good agreement with previous modeling studies. The storm surges induced by four historical hurricanes (Rita, Katrina, Ivan, and Dolly) were simulated and compared to observed water levels at National Oceanic and Atmospheric Administration tide stations. Effects of coastal subsidence and future global sea-level rise on coastal inundation in the Louisiana coast were evaluated using a “change of inundation depth” parameter through sensitivity simulations that were based on a projected future subsidence scenario and 1-m global sea-level rise by the end of the century. Model results suggested that hurricane-induced storm surge height and coastal inundation could be exacerbated by future global sea-level rise and subsidence, and that responses of storm surge and coastal inundation to the effects of sea-level rise and subsidence are highly nonlinear and vary on temporal and spatial scales.     

On the influence of changes in the drag relation on surface wind speeds and storm surge forecasts

In this study it is investigated how uncertainties in the magnitude of the drag coefficient translate into uncertainties in storm surge forecasts in the case of severe weather. A storm surge model is used with wind stress data from a numerical weather prediction (NWP) model, to simulate several recent storms over the North Sea. For a fixed wind speed, the wind stress is linear in the drag coefficient. However, in the NWP model the wind speed is not fixed and increasing the drag in the NWP model results into reduced wind speeds. The results from simulations show that for given increase in the drag coefficient, the weakening of the 10-m wind field reduces the increase in the stress considerably. When the Charnock parameter is increased in the NWP model, the resulting relative changes in the wind stress are almost independent of the wind speed. This is related to the fact that the depth of the surface boundary layer depends on the wind speed. The ratio between relative changes in the wind stress and relative changes in the drag coefficient depends on the wind speed. For 10-m wind speeds larger than 20?m?s^?1 the ratio is 0.52; for lower wind speed criteria the ratio is somewhat larger (??0.60). Approximately 36% of the relative change in the drag coefficient translates into a relative change in the surge in stations at the Dutch coast. The relative increase in the storm surge is approximately 68% of the relative increase in the stress.     

Simultaneous meteorological tsunamis and storm surges at Buenos Aires coast,southeastern South America

Meteorological tsunamis are frequently observed in different tide stations at the southeastern coast of South America. They are associated with the occurrence of atmospheric gravity waves during the passages of cold fronts over the Buenos Aires Province continental shelf. On the other hand, storm surges are also frequent in the region, and they are associated with strong and persistent southerlies, which are also frequent during cold front passages. The impact of meteorological tsunamis in coastal erosion and in the statistics of storm surge trends is discussed in this paper. For this study, fifteen meteorological tsunamis (with maximum wave heights higher than 0.20 m), seven of them simultaneous to the occurrence of storm surge events (with extreme levels higher than |±0.60 m|), are selected from April 2010 to January 2013. The impact of meteorological tsunamis in the storm erosion potential index (SEPI) is evaluated. Not significant differences are obtained between SEPI calculated with and without filtering the meteorological tsunami signal from the storm surge data series. Moreover, several experiments are carried out computing SEPI from synthetic sea level data series, but very low changes (lower than 4 %) are also obtained. It is concluded that the presence of moderate meteorological tsunamis on sea level records would not enhance this index at the Buenos Aires Province coast. On the other hand, taking into account that meteorological tsunamis can reach up the 20–30 % of the storm surge height, it was concluded that the statistics of storm surge trends (and their uncertainties) should be revised for Mar del Plata data series.     

Correction to: Tropical cyclone: expressions for velocity components and stability parameter

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.     

Modeling the impact of land reclamation on storm surges in Bohai Sea,China

A nested model for the simulation of tides and storm surges in the Bohai Sea, China, has been developed based on the three-dimensional finite-volume coastal ocean model. The larger domain covers the entire Yellow Sea and Bohai Sea with a horizontal resolution of ~10 km, and the smaller domain focuses on the Bohai Sea with a fine resolution up to ~300 m. For the four representative storm surges caused by extratropical storms and typhoons, the simulated surge heights are in good agreement with observations at coastal tide gauges. A series of sensitivity experiments are carried out to assess the influence of coastline change due to land reclamation in recent decades on water levels during storm surges. Simulation results suggest that changes in coastline cause changes in the amplitude and phase of the tidal elevation, and fluctuations of surge height after the peak stage of the storm surges. Hence, for the assessment of the influence of coastline changes on the total water level during storm surges, the amplitudes and phases of both the tidal and surge heights need to be taken into account. For the three major ports in the Bohai Bay, model results suggest that land reclamation has created a coastline structure that favors increasing the maximum water level by 0.1–0.2 m. Considering that during the storm surges the total water level is close to or even exceeds the warning level for these ports, further increasing the maximum water level by 0.1–0.2 m has the potential to cause severe damages and losses in these ports.

     

Extremity analysis of storm surge for fixing safe design water level

Phenomenal storm surge levels associated with cyclones are common in East Coast of India. The coastal regions of Andhra Pradesh are in rapid stride of myriad marine infrastructural developments. The safe elevations of coastal structures need a long-term assessment of storm surge conditions. Hence, past 50 years (1949–1998), tropical cyclones hit the Bay are obtained from Fleet Naval Meteorological & Oceanographic Center, USA, and analyzed to assess the storm surge experienced around Kakinada and along south Andhra Pradesh coast. In this paper, authors implemented Rankin Hydromet Vortex model and Bretschneider’s wind stress formulation to hindcast the surge levels. It is seen from the hindcast data that the November, 1977 cyclone has generated highest surge of the order of 1.98 m. Extreme value analysis is carried out using Weibull distribution for long-term prediction. The results reveal that the surge for 1 in 100-year return period is 2.0 m. Further the highest surge in 50 years generated by the severe cyclone (1977) is numerically simulated using hydrodynamic model of Mike-21. The simulation results show that the Krishnapatnam, Nizampatnam and south of Kakinada have experienced a surge of 1.0, 1.5 and 0.75 m, respectively.     

Numerical simulation of storm surges in Lake Winnipeg

A high-resolution unstructured grid two-dimensional finite-element model was applied to simulate the storm surge associated with the October 2010 extratropical storm in Lake Winnipeg. The wind and pressure fields from two high-resolution weather forecast models were used to drive the hydrodynamic model. The model results were compared with the observed water levels at several stations during the storm event. The model-predicted storm surge in the range of 0.6–1.5 m is comparable with observations in the southern basin of Lake Winnipeg. Model results are further analyzed to assess the transport of water between north and south basins of Lake Winnipeg during the event. Computed water surface elevations at specific locations at the outlet of the rivers and embayments indicate that the model needs some improvements in terms of grid resolution in those areas.     

Estimation of property loss and business interruption loss caused by storm surge inundation due to climate change: a case of Typhoon Vera revisit

This paper estimates property loss and business interruption loss under scenarios of storm surge inundation to explore the economic impact of climate change on Ise Bay, Japan. Scenarios-based analyses are conducted with respect to Typhoon Vera, which caused the most severe storm surge in the recorded history of Japan in 1959. Four different hazard scenarios are chosen from a series of typhoon storm surge inundation simulations: Typhoon Vera’s landfall with respect to the condition of the past seawall; Typhoon Vera’s landfall with respect to the condition of the current seawall; intensifying Typhoon Vera, but retaining its original tracks; and intensifying Typhoon Vera, but choosing the worst tracks from various possible typhoon tracks. Our economic loss estimation takes advantage of fine geographical scale census and economic census data that enable us to understand the spatial distribution of property loss and business interruption loss as well as identify the most potentially affected areas and business sectors on a sub-city scale. By comparing the property loss and business interruption loss caused by different hazard scenarios, the effect of different seawalls is evaluated and the economic impact of future climate change is estimated. The results indicate that although the current seawall can considerably reduce the scale of losses, climate change can cause Ise Bay to experience more serious storm surge inundation. Moreover, the resulting economic losses would increase significantly owing to a combination of climate change and the worst track scenario. It is, therefore, necessary to consider more countermeasures to adapt to climate change in this area.

     

Numerical simulation and prediction of storm surges and water levels in Shanghai harbour and its vicinity

A water level model incorporating the nonlinear interactions between tides and storm surges for numerical simulation and prediction use is developed in this paper. Using a conventional two-dimensional nonlinear storm surge model and tide model and associated semi-momentum finite-difference scheme, both the storm surges caused by the tropical cyclones hitting Shanghai and the tides in related regions during the period 1949–1990, are numerically simulated. In simulating storm surges, 16 tropical cyclones with different kinds of tracks are chosen. Meanwhile, to simulate tides, the governing equations for tides, along with 63 prescribed tidal constituents at open sea boundaries are numerically computed. Sixteen associated cases of total water-level simulations comprising joint effects linking surges and tides and one case of real-time prediction have been carried out in 1990 on the basis of computed surges and tides. The total water levels thus obtained in this way give better results than those obtained by the traditional method, i.e. without taking into account, in the model, nonlinear coupling between storm surges and tides.Comparison of the predictions of storm surges and the total water level with the hindcast ones in 1990 showed that a relatively larger error of prediction mainly results from the incorrect forecasting of tropical cyclones but not from the prediction method itself.     

Application of a fast stochastic storm surge model on estimating the high water level frequency in the Lower Rhine Delta

In the Lower Rhine Delta of the Netherlands, the high water level is driven by a joint impact of the downstream storm surge and the upstream fluvial discharge, and affected by the operation of existing man-made structures. In scenario-based risk assessment, a large number of stochastic scenarios of storm surges are required for estimating the high water level frequency. In this article, a fast computing stochastic storm surge model is applied to the gauge station of Hook of Holland in the west of the Netherlands. A fixed number of tides are considered in this model based on the information of historical storm surge events. Based on this model, a large number of stochastic storm surge scenarios are derived and forced into a one-dimensional hydrodynamic model of the Netherlands, resulting in peak water levels in Rotterdam, the most vulnerable city in the delta. These peak water levels are statistically analyzed and converted to the high water level frequency curve in Rotterdam. The high water level frequency curve in Rotterdam tends to a much lower design water level compared to the official design water level that is used to design the dikes and structures for protection of the city. Moreover, there is a significant difference in the high water level frequency curves due to the fact that the stochastic storm surge model considers different numbers of tides. This highlights the critical impact of the storm surge duration on the high water level frequency in the Lower Rhine Delta.     

渤海湾西部风暴潮漫滩数值模拟

基于ROMS海洋模式,结合近年的地质实测资料,建立了渤海湾西部地区风暴潮漫滩的数值模型。对模型进行验证后,对渤海湾西部区域重现期为50a、100a、200a及500a的风暴潮漫滩进行了数值模拟,分析了不同重现期风暴潮漫滩发展的动态过程及最大漫滩淹水范围。结果表明,数值模型基本能反映风暴潮的增水趋势,能够模拟风暴潮漫滩发生发展的动态过程。随着风暴潮强度的增加,渤海湾西部地区淹水范围具有从东海岸向西部内陆区域扩展的趋势。通过曲线拟合发现,风暴潮最大漫滩面积比值与高水位之间基本呈线性关系。