Extreme Wave Heights Research Articles

The Effect of Bulbous Bow on the Probability of Slamming on Hull (Case Study on Container vessel 4200 DWT)

One of the environmental factors that influence the probability of a ship accident is the wave height. Extreme wave height can cause the bow of the ship crashing on the surface of the sea water (slamming). Slamming can cause local buckling and deformation on the ship’s bottom plate at the bow. At certain conditions the slamming can cause damage to the ship’s bow structure. This research discussed the effect of using bulbous bow on slamming probability on 4200 DWT container vessel. The analysis was carried out at 1.5 - 3 meter wave height conditions, according to the wave height conditions on this ship’s shipping route in Makassar Strait. The geometrical dimension is LPR = 2.116 m, BB = 2.805 m and ZB = 2,42 m. The analysis of the motion response of the ship is carried out on two types of motion heaving and pitching. In maximum draft conditions, 5.5 meters and speed 11.9 knots (6.12 m/s) and a heading angle of 180°. The next step is calculation of response spectrum by multiplying the wave spectrum with RAO. From the analysis, known that higher wave produced greater response of heaving and pitching motion. And also higher wave produced higher relative bow motion spectrum. The probability of slamming of 4200 DWT ships with bulbous bow is smaller than without bulbous bow. At a certain wave height (2-3 meters) indicates that the bulbous bow reduces the slamming probability approximately 17-49%. The intensity slamming per hour of 4200 DWT ships with bulbous bow is smaller than without bulbous bow. It is indicates that the bulbous bow reduces the slamming intensity per hour approximately 24-45%.

Increasing Historical Tropical Cyclone-Induced Extreme Wave Heights in the Northern East China Sea during 1979 to 2018

Tropical cyclone (TC)-induced wind waves are a major concern in coastal safety, therefore quantifying the long-term change in extreme TC waves is critical for the design of coastal infrastructures and for understanding variations in coastal morphology. In this study, a trend analysis is performed on the TC-induced extreme wave heights in the northern East China Sea using numerically simulated wave height data during the period of 1979 to 2018. The simulation was forced with historical TC winds constructed using a parametric TC wind model with satellite-observed TC best-track data as the input. The results show consistently increasing extreme wave heights throughout the study region, which are induced predominantly by the increasing TC intensity. The increase rates (0.01–0.08 m yr−1) are relatively large (small) in offshore (nearshore) waters and at relatively high (low) latitudes. The spatial variability of the wave height trend is highly sensitive to the type of TC track. An analytical model of extreme wave height trend is developed that can efficiently estimate the rate of change in the extreme wave heights using extreme wind speed information.

Correlation of Concurrent Extreme Metocean Hazards Considering Seasonality

Simultaneous occurrence of metocean variables can present a multihazard to maritime systems. However, simplified design approaches to assess simultaneous significant wave heights and wind velocities are lacking, especially if seasonality is considered. This is addressed in this study by using extreme significant wave heights and companion wind velocities recorded in the Gulf of Mexico. Time-dependent, generalized extreme value (GEV) models and classical regression are the basis to propose a simplified approach to estimate correlated extreme significant wave heights and wind velocities associated with given return periods, accounting for seasonality and including measures of uncertainty. It is found that the proposed approach is a new but simple method to adequately characterize the concurrent extreme metocean variables and their uncertainty. It is concluded that the method is an effective probabilistic design tool to determine simultaneous extreme significant wave heights and companion wind velocities for desired return periods and seasonality.

Extreme Significant Wave Height of Western and Central Indonesian Seas and Its Correlation with ISO 19901-1:2015

Extreme significant wave height is a commonly used parameter for designing offshore structures. ISO provides general extreme significant wave height information of six ocean regions in the world, including the Southern East Asian Sea. However, for the case of Indonesia, ISO only includes the Natuna Sea region. One of the qualified datasets that provide significant wave height data for Indonesian seas is SEAFINE by Oceanweather, Inc. This dataset covers the western and middle part of Indonesia. We analyzed the SEAFINE significant wave height hindcast data in these regions to obtain the extreme values. Extreme significant wave height maps were then produced based on the analyzed data. For the purpose of validation, we compared the extreme value analysis result with ISO 19901-1:2015 in regions where SEAFINE and ISO data intersect. The comparison showed that the analysis result tends to give approximately 25% lower wave height for a 1-year return period compared to ISO 19901-1:2015 but agreement for a 100-year return period. The SEAFINE analysis result also shows agreement with previous studies in the Karimata Strait and the Java Sea.

Bivariate regional extreme value analysis for significant wave height and wave period

This paper presents a bivariate regional frequency analysis applied to vectors of extreme significant wave heights and concurrent zero up-crossing wave period over an area in the North Atlantic ocean. The analysis is based on a bivariate index-wave/period approach and the assumption of a common regional growth curve within homogeneous regions. The main benefits of performing a regional frequency analysis as opposed to at-site analysis based on data from one location only are twofold: It may give more accurate predictions of extreme conditions due to the increased amount of data made available for the statistical analysis, and results for ungauged locations can be obtained easily by interpolation of the index wave/period. Previous regional frequency analyses for ocean waves have been restricted to the univariate case. However, design conditions for marine and coastal structures will typically be characterised by the joint distribution of several metocean variables. Hence, it is useful to perform multivariate analyses of the extreme ocean environment. As a minimum, information about the joint distribution of significant wave height and period is often needed. This paper outlines the various steps involved in a bivariate regional frequency analysis and presents the results of such an analysis applied to data covering the North Atlantic ocean over a period of 30 years.

Assessment of storm events along the Algiers coast and their potential impacts

Knowledge of coastal storm regimes is essential to ensure an economic and sustainable development in the coastal area. In recent decades, wave storms have been responsible for several fatalities and economic losses along the Algiers coast. The aim of this paper is to present a detailed analysis on wave storm events during the past 40 years, including an assessment of the potential impacts of various storm events along the Algiers coasts according to their intensity and direction based on the different historical events. Thus, this paper gives an estimation of return periods of extreme significant wave heights and extreme storm events. For this purpose, the wave storm events occurring in the Algiers coasts, based on the storm power index (SPI) developed by Dolan and Davis (1992), were characterized and classified. Five storm categories were defined in terms of their power index, subdivided into 31 categories, taking into consideration their propagation directions. The temporal analysis shows a progressive increase in the number of storm events and their intensity during the last decade, which explains the increased damage recorded recently in the Algiers coastlines. A spatial analysis of these extreme and catastrophic storms being responsible in these damages has shown that the nature of coastal storm damages on the local scale depends on several factors, mainly power of these storms and their direction; in view of the complex morphology of the Algiers coastlines. These two factors were considered during the extreme value analysis, and allowed us to estimate the return period of the storm events already observed based on their SPI and direction. A return period of 59 years has been estimated for the catastrophic storm of 2015, which caused significant erosion resulting a loss of more than 15 000 m2 of coastal lands.

Attribution of Extreme Wave Height Records along the North Atlantic Coasts using Hindcast Data: Feasibility and Limitations

Rohmer, J.; Louisor, J.; Le Cozannet, G.; Naveau, P.; Thao, S., and Bertin, X., 2020. Attribution of extreme wave height records along the North Atlantic coasts using hindcast data: Feasibility and limitations. In: Malvarez, G. and Navas, F. (eds.), Global Coastal Issues of 2020. Journal of Coastal Research, Special Issue No. 95, pp. 1268-1272. Coconut Creek (Florida), ISSN 0749-0208.Extreme Event Attribution (EEA) aims at answering questions about how much climate change influenced the probability or intensity of a specific type of extreme meteo-oceanic event. Here, we focus on wave record breaking i.e. the occurrence of an extreme significant wave height (hs) value that exceeds all past observations. The objective is to evaluate the probability changes related to climate change by estimating the fraction of attributable risk far=1–p0/p1, where p0 and p1 are probabilities of the wave record event in two different worlds: a counterfactual world without anthropogenic forcings i.e. a “world that might have been”, and the factual world, i.e. “world that is.” To define these different worlds, we rely on a wave hindcast database, which provides very long time series (1900-2008) of hs over the whole North Atlantic Ocean Basin (NAOB). We assume that the counterfactual world corresponds to the series of annual hs maxima over the period 1900-1930, and that the factual world corresponds to the annual hs maxima over the period 1978-2008. The extreme event attribution approach dedicated to record breakings was applied over NAOB, and we show large far values (>0.5) along the northern Canadian, Scottish and southwestern Norwegian coasts (over the latitudes 50°-65°N). These results are, however, carefully discussed with respect to different uncertainty sources, namely the validity of the assumptions underlying the EEA, the statistical uncertainties, the use of hindcast data instead of global climate model's results, and the limitations in the hindcast database setup.

SEM-REV offshore energy site wind-wave bivariate statistics by hindcast

Accurate estimation of extreme wind and wave conditions is critical for ocean engineering activities and applications. Various renewable energy offshore structures, particularly floating wind turbines are designed to sustain extreme wind and wave induced loads. Statistics of wind speeds and wave heights is the key input for structural safety and reliability study. Consequently, development of novel robust methods, able to predict extreme wind-wave conditions is essential.This paper discusses criteria for selecting design point by applying recently developed method for estimating extreme wave statistics, based on the hourly wave height and wind speed maxima at the location of interest. Wave and wind data, analyzed in this paper, was obtained from the hindcast model applied to the SEM-REV offshore sea location, near the coast of France, during years 2001–2010. The ECMWF (European Centre for Medium range Weather Forecasting) framework along with the atmospheric model SKIRON were employed to generate accurate hindcast wind-wave hourly data at the location of interest. Note that the SEM-REV site was built within the framework of the CPER (Contrat de Projet Etat-Région) 2007–2013 for the Pays de la Loire region, therefore it is important to note that 2001–2010 data studied in this paper was obtained by hindcast into the time period before SEM-REV began operations.Structural design values are often based on univariate statistical analysis, while actually multivariate statistics is more appropriate for modelling the whole structure. The bivariate analysis of extremes is often poorly understood and generally not adequately considered in most practical measurements/situations, therefore it is important to utilize recently developed bivariate average conditional exceedance rate (ACER2D) method.This paper studies extreme wind speeds and wave heights, that are simultaneously obtained at the same location. Due to less than full correlation between wind speed and wave height, application of the multivariate, or bivariate in the simplest case, extreme value theory is of practical importance. This paper focuses on application of the bivariate ACER2D method for prediction of bivariate extreme value statistics.Finally, this paper suggests how the design point should be chosed based on bivariate analysis. The latter is of particular engineering importance as it presents first application of bivariate wind-wave statistics to a raw SEM-REV site data.

Characterization of Extreme Wave Conditions for Wave Energy Converter Design and Project Risk Assessment

Best practices and international standards for determining n-year return period extreme wave (sea states) conditions allow wave energy converter designers and project developers the option to apply simple univariate or more complex bivariate extreme value analysis methods. The present study compares extreme sea state estimates derived from univariate and bivariate methods and investigates the performance of spectral wave models for predicting extreme sea states at buoy locations within several regional wave climates along the US East and West Coasts. Two common third-generation spectral wave models are evaluated, a WAVEWATCH III® model with a grid resolution of 4 arc-minutes (6–7 km), and a Simulating WAves Nearshore model, with a coastal resolution of 200–300 m. Both models are used to generate multi-year hindcasts, from which extreme sea state statistics used for wave conditions characterization can be derived and compared to those based on in-situ observations at National Data Buoy Center stations. Comparison of results using different univariate and bivariate methods from the same data source indicates reasonable agreement on average. Discrepancies are predominantly random. Large discrepancies are common and increase with return period. There is a systematic underbias for extreme significant wave heights derived from model hindcasts compared to those derived from buoy measurements. This underbias is dependent on model spatial resolution. However, simple linear corrections can effectively compensate for this bias. A similar approach is not possible for correcting model-derived environmental contours, but other methods, e.g., machine learning, should be explored.

Uncertainties of Estimating Extreme Significant Wave Height for Engineering Applications Depending on the Approach and Fitting Technique—Adriatic Sea Case Study

Studies on the extrapolation of extreme significant wave height, based on long-term databases, are extensively covered in literature. An engineer, working in the field of naval architecture, marine engineering, or maritime operation planning, when tackling the problem of extreme wave prediction, would typically follow relevant codes and standards. Currently, authorities in the field of offshore operation within its guidelines propose several methods: the initial-distribution, extreme value, and peak-over threshold approaches. Furthermore, for each proposed method, different mathematical fitting techniques are applicable to optimize the candidate distribution parameters: the least-square method, the method of moments, and the maximum likelihood method. A comprehensive analysis was done to determine the difference in the results depending on the choice of method and fitting technique. All combinations were tested on a long-term database for a location in the Adriatic Sea. The variability of the results and trends of extreme wave height estimates for long return periods are presented, and the limitations of certain methods and techniques are noted.

Oil rig protection against wind and wave in Lebanon

The oil rigs that will be installed in the Lebanese offshore are floating rigs. This type can be affected by environmental risks such as extreme wind speed and wave height. We study these risks in Beddawi region in the northern Lebanon during the winter season by applying the extreme value theory to real data. We estimate at a first stage the return levels associated to return periods of 50, 100, and 500 years for each risk separately using the classical univariate theory. At a second stage, we use the logistic parametric model and the bivariate copula functions in multivariate extreme value theory to estimate the dependence between extreme wind speed and wave height as well as joint exceedance probabilities and joint return levels to take into consideration the risk of these two environmental factors simultaneously.

Study of Directional Declustering for Estimating Extreme Wave Heights in the Yellow Sea

The study of extreme waves is important for the protection of coastal and ocean structures. In this work, a 22-year (1990–2011) wave hindcast in the Yellow Sea is employed to perform the assessment of extreme significant wave heights in this area. To extract the independent sample from this database, the fixed window method is used, which takes the peak significant wave height within five d. With the selected samples, directional declustering is studied to extract the homogenous sample. The results show that most of the independent samples (especially large samples) are observed in the North. In this direction, the peak over threshold (POT) method is used to extract the extreme sample from the homogenous sample, and then the generalized Pareto distribution model is used to extrapolate the extreme significant wave height. In addition to this combination, the annual maxima method with the Gumbel model is also used for estimating extreme values. The comparisons show that the return significant wave heights of the first combination are reliable, resulting from a flexible sampling window in the POT method. With this conclusion, the extreme significant wave height is extrapolated from the Yellow Sea, which can be used to protect the structure in the main directional bin.

Numerical Study of the Impact of Climate Change on Irregular Wave Run-up Over Reef-Fringed Coasts

Wave hydrodynamics over fringing reefs is largely controlled by the reef surface roughness and hydrodynamic forcing. It is believed that climate change will result in a net increase in the water depth over the reef flat, a degrading of the surface roughness of coral reefs and changes in extreme incident wave heights. For an accurate assessment of how climate change affects the safety of reef-fringed coasts, a numerical study of the impact of climate change on irregular wave run-up over reef-fringed coasts was carried out based on a Boussinesq wave model, FUNWAVE-TVD. Validated with experimental data, the present model shows reasonable prediction of irregular wave evolution and run-up height over fringing reefs. Numerical experiments were then implemented based on the anticipated effects of climate change and carried out to investigate the effects of sea level rise, degrading of the reef surface roughness and increase of extreme incident wave height on the irregular wave run-up height over the back-reef beach respectively. Variations of run-up components (i.e., spectral characteristics of run-up and mean water level) were examined specifically and discussed to better understand the influencing mechanism of each climate change-related effect on the run-up.

Extracting independent and identically distributed samples from time series significant wave heights in the Yellow Sea

The assessment of extreme significant wave heights is crucial for the design of coastal defences and offshore infrastructures, which requires independent and identically distributed samples to be extracted. To extract independent samples at the regional scale, an automated method is proposed by extending an observational method. In addition to the initial threshold, a minimum interval is used to identify two consecutive storms with a long storm interval, and a minimum level is used to distinguish one storm with a small fluctuation around the initial threshold from two consecutive storms with a short storm interval. By using this method, independent samples in the Yellow Sea are extracted from a 40-year (1979–2018) hindcast of significant wave heights. In this area, storms during tropical cyclones are generally strong, and most storms are driven by winter storms. Comprehensively considering the storm intensity and frequency, the independent sample is divided by an automated method into homogenous samples 1 and 2, depending on the tracks and recorded times of tropical cyclones. Homogenous samples 1 and 2 represent the independent samples in the tropical cyclone and non-tropical cyclone, respectively. Within homogenous sample 2, most independent samples (especially large independent samples) are observed in oceanographic winter. In addition, the difference between the return significant wave heights based on homogenous sample 2 and those based on the winter storm sample is very small. Thus, seasonal declustering is not performed on homogenous sample 2. Consequently, by utilizing the independent and identically distributed samples extracted by two automated methods, a regional analysis of the extreme significant wave heights in the Yellow Sea is performed.

Directional Extreme Value Models in Wave Energy Applications

A wide range of wave energy applications relies on the accurate estimation of extreme wave conditions, while some of them are frequently affected by directionality. For example, attenuators and terminators are the most common types of wave energy converters whose performance is highly influenced by their orientation with respect to the prevailing wave direction. In this work, four locations in the eastern Mediterranean Sea are selected with relatively high wave energy flux values and extreme wave heights are examined with wave direction as a covariate. The Generalized Pareto distribution is used to model the extreme values of wave height over a pre-defined threshold, with its parameters being expressed as a function of wave direction through Fourier series expansion. In order to be consistent with the analysis obtained from the independent fits for directional sectors, the estimation of parameters is based on a penalized maximum likelihood criterion that ensures a good agreement between the two approaches. The obtained results validate the integration of directionality in extreme value models for the examined locations and design values of significant wave height are provided with respect to direction for the 50- and 100-year return period with bootstrap confidence intervals.

Skill Assessment of an Atmosphere–Wave Regional Coupled Model over the East China Sea with a Focus on Typhoons

This study performed several sensitivity experiments to investigate the impact of atmosphere–wave coupling on the simulated wind and waves over the East China Sea (ECS) with a focus on typhoon events. These experiments include stand-alone regional atmosphere model (CCLM) simulations, stand-alone spectral wave model (WAM) simulations driven by the regional atmospheric model CCLM or ERA5 reanalysis, and two-way (CCLM-WAM) coupled simulations. We assessed the simulated wind speed and significant wave height against in situ observations and remote sensing data and focused on typhoon events in 2010. We analyzed the differences between the experiments in capturing the surface pressure, wind speed, and roughness length. Both ERA5 reanalysis data and our regional model simulations demonstrate high quality in capturing wind and wave conditions over the ECS. The results show that downscaled simulations tend to be closer to in situ observations than ERA5 reanalysis data in capturing wind variability and probability distribution, dominant wind and wave directions, strong typhoon intensity and related extreme significant wave height. In comparison with satellite observations, the CCLM-WAM simulation outperforms the CCLM in reducing wind bias. The coupled and uncoupled simulations are very similar in terms of other wind and wave statistics. Though there is much improvement in capturing typhoon intensity to ERA5, regional downscaled simulations still underestimate the wind intensity of tropical cyclones.

Improving Coastal Ocean Wave Height Forecasting during Typhoons by using Local Meteorological and Neighboring Wave Data in Support Vector Regression Models

This study is aimed at applying support vector regression to perform real-time typhoon wave height forecasting with lead times of 1 to 3 h. Two wave rider buoys in the coastal ocean northeast of Taiwan provided real-time observation wave and meteorological data for the study. Information from actual typhoon events was collected and used for model calibration and validation. Three model structures were developed with different combinations of input variables, including wave, typhoon, and meteorological data. Analysis of forecasting results indicated that the proposed models have good generalization ability, but forecasts with longer lead times underestimate extreme wave heights. Comparisons of models with different inputs indicated that adding local meteorological data enhanced forecasting accuracy. Backup models were also developed in case local wave and meteorological data were unavailable. Analysis of these models revealed that when local wave heights are unknown, using neighboring wave heights can improve forecasting performance.

Wave crest height distribution during the tropical cyclone period

The wave crest height plays a vital role in designing both the fixed and floating marine structures. The present study examines the measured wave crest data at 18 m water depth off Visakhapatnam in the northwestern Bay of Bengal during the tropical cyclone (TC) Hudhud. The maximum significant wave height (Hs) measured during the TC is 7.59 m on 12 October 2014 at 1030 h; the maximum wave height is 10.75 m and the crest height is 6.81 m. The average ratio of the crest height of the wave to the wave height is 0.4–0.7 during the TC. For waves with Hs more than 6 m, the most extreme wave height is 1.46–1.83 times the Hs and the crest height of the wave is 0.81–1.47 times the Hs of the same 30-min record. The study shows that during the high wave events, the Weibull distribution agrees with the crest height distribution of observed data better than the Rayleigh distribution.

Proposed a New Hybrid LOF-ANN Method to Extreme Wave Height Prediction based on Meteorological Data

Proposed a New Hybrid LOF-ANN Method to Extreme Wave Height Prediction based on Meteorological Data

ВЕТРО-ВОЛНОВОЙ КЛИМАТ КАСПИЙСКОГО МОРЯ

The modern approach for wind wave climate estimation is presented. The input for wave calculation by numerical models is reanalysis data. For extreme wave estimation in severe storms the reanalysis data has to be corrected (by regression model as an example). For calculations of wind waves in Caspian Sea SWAN model was used. 40 years continues calculations were made. At the first stage calculations performed for whole the sea, and then these data were used as the first input for detailed calculations for shallow the Northern Caspian Sea. The estimates of extreme wave heights were presented for different depths.