Wave Heights For Return Periods Research Articles

Understanding uncertainties in contemporary and future extreme wave events for broad-scale impact and adaptation planning.

Understanding uncertainties in extreme wind-wave events is essential for offshore/coastal risk and adaptation estimates. Despite this, uncertainties in contemporary extreme wave events have not been assessed, and projections are still limited. Here, we quantify, at global scale, the uncertainties in contemporary extreme wave estimates across an ensemble of widely used global wave reanalyses/hindcasts supported by observations. We find that contemporary uncertainties in 50-year return period wave heights ([Formula: see text]) reach (on average) ~2.5m in regions adjacent to coastlines and are primarily driven by atmospheric forcing. Furthermore, we show that uncertainties in contemporary [Formula: see text] estimates dominate projected 21st-century changes in [Formula: see text] across ~80% of global ocean and coastlines. When translated into broad-scale coastal risk analysis, these uncertainties are comparable to those from storm surges and projected sea level rise. Thus, uncertainties in contemporary extreme wave events need to be combined with those of projections to fully assess potential impacts.

Extreme value analysis for waves in the Persian Gulf: Skill assessment of different methods for a fetch-limited basin

Estimating the design wave height with specific return period using extreme value analysis (EVA) is of significant importance in coastal and marine engineering. The purpose of this study is to compare different methods such as the Maximum Likelihood, the L-Moment and the least square methods to estimate the parameters of Generalized Pareto Distribution (GPD), Gumbel, and Weibull distributions in order to determine 100 years return period wave height at 16 selected points within the Persian Gulf. The Peaks Over Threshold (POT) method was employed for all tests. The hourly wave data were available for the total period of 30 years from 01/01/1990 to 31/12/2019 using reanalyzed ECMWF-ERA5 dataset as well as hindcast results from a calibrated local WAVEWATCH-III model. In order to find the threshold cutoff value, one of the pivotal parameters in EVA, adaptive approaches were employed which determined the threshold value based on the distribution function and the goodness of fit for extreme data at specific site. It was shown that subjective constant values used in most of previous studies in this water body were much less than what should be used to have the best fit. Moreover, the determined threshold value was not constant at different points and varied depending on the type of distribution employed. The results showed superiority of the Gumbel distribution in most of the points in the Persian Gulf. Sensitivity Analysis to the threshold values showed that using a low threshold value would lead to increasing the return wave height, which was significant in the case of Pareto and Gumbel distributions. Sensitivity analysis to input data confirmed that ECMWF-ERA5 underestimated the wave height and consequently, the underestimation of designed wave height at some locations by more than 40%. Also, the results from Annual Maxima Method (AMM) was similar to POT method but with ±20% differences in values.

Influence of tropical cyclones on the 100‐year return period wave height—A study based on 39‐year long ERA5 reanalysis data

AbstractVarious engineering activities in a coastal and offshore environment require detailed assessment about the probable extreme wave characteristics in its lifetime to prevent human as well as property loss. The accurate estimation of wave height with a 100‐year return period not only contribute to the level of protection but also the scale of investments. In this study, significant wave height return levels for a northwestern Bay of Bengal location are estimated using extreme value models; generalized extreme value (GEV) and generalized Pareto distribution (GPD). Both block maxima and initial distribution methods are used in the GEV and GPD incorporated with peak over threshold (POT) series. The study is based on the European Centre for Medium‐Range Weather Forecasts ERA5 reanalysis hourly data at 0.25° × 0.25° spatial resolution from 1979 to 2017. The GPD estimates show that the return levels do not follow prevailing seasonality over the location since the return levels greatly depend upon the extreme events and most of the extreme events are during the northeast monsoon season (October–January). The POT with October–January data gives 9.08 m as 100‐year return level, and corresponding Indian southwest monsoon (June–September) return level is only 5.41 m. When different block periods ranging from 15 to 39 years are considered, the 50‐year return levels range from 5.12 to 8.67 m for GEV with annual maxima. The influence of tropical cyclones (TCs) on return levels are examined considering different case studies, and the results show that the strength of a TC alters the return levels more significantly than the number of TCs in the observation. The 100‐year return level decreases by ~30% when wave height during the two cyclones; Phailin and Hudhud are removed from the data set.

Investigation of trends in extreme significant wave heights in the South China Sea

The focus of this study was the temporal and spatial variations of extreme significant wave heights and nearshore return-period wave heights in the South China Sea, based on the wave model and European Reanalysis-Interim data from 1979–2016. Measured buoy data were available from near Yongxing Island for comparison with the reanalysis data during the passage of typhoons. Annual maximum significant wave heights showed a statistically significant increasing trend over most of the South China Sea, whereas statistically insignificant decreasing or increasing trends were observed for seasonal maximum significant wave heights associated with the different characteristics of the typhoon events. Nonstationary generalized extreme value analysis was used to investigate the influence of nearshore extreme significant wave heights derived from the Simulating Waves Nearshore model at four offshore locations in the South China Sea. The fastest increase of 100-year return significant wave heights was found to be 0.0033 m yr−1 in the western South China Sea. The results show that, in recent decades, no significant variation trends can be found in return-period wave heights at nearshore of South China Sea, which may be related to tracks of intense typhoons in the region.

System Reliability Assessment of Existing Jacket Platforms in Malaysian Waters

Reliability of offshore platforms has become a very important issue in the Malaysian Oil and Gas Industry as, majority of the jacket platforms in Malaysian waters to date, have exceeded their design life. Reliability of a jacket platform can be assessed through reliability index and probability of failure. Conventional metocean consideration uses 100 year return period wave height associated with 100 year return period current velocity and wind speed. However, recent study shows that for Malaysian waters, the proposed metocean consideration should be 100 year return period wave height associated with 10 year return period current velocity and wind speed. Hence, this research investigated the effect of different metocean consideration, to system-based reliability of jacket platforms in Malaysian waters. Prior to that, the effect of different metocean consideration to the pushover analysis has also been studied. Besides, the significance of Pile Soil Interaction (PSI), wave direction and platform geometry were analyzed in a sensitivity study. Pushover analysis was performed on three jacket platforms representing three water regions in Malaysia to obtain Reserve Strength Ratio (RSR) as an indicator of the reliability of the jackets. Utilizing sensitivity study parameters mentioned above, seven different case studies were undertaken to study their significance on RSR. The RSR values of each case study were compared and incorporated as resistance model of reliability analysis. Besides, platform specific response model of each jacket has been generated using response surface technique which was later incorporated into the limit state function for reliability analysis. Reliability analysis using First Order Reliability Method (FORM) has been conducted in MATLAB to obtain the reliability index and probability of failure. Results from the reliability analysis were compared to analyze the effect of different metocean consideration. In this study, an updated and detailed methodology of system reliability analysis for offshore jacket platforms is presented. Relationship curves for the safety indices were generated as the outcome of this study. Probability of Failure is found to be inversely functional to RSR. The newly proposed metocean consideration eliminates the conservativeness in currently practiced metocean values. Parameters like metocean considerations and PSI greatly affect the RSR, hence affects Reliability index and Probability of Failure.

Estimation of design wave height using empirical simulation technique

In this study, we applied the empirical simulation technique (EST) to the estimation of deepwater design wave heights in several areas in the South Coast of Korea. For the historical typhoons that impacted each area during 59 years from 1951 to 2009, numerical simulations were performed to calculate the wave fields. The simulation results were then used for the generation of the training sets of the EST. The results of the EST were compared with those of the least squares method (LSM) used along with the peaks-over-threshold method. For the 50-year return period wave heights, the EST estimated larger values than the LSM by 2%–26%. If the difference between the EST and the LSM is small for the 50-year return period wave height, the LSM and the EST estimate similar wave heights throughout the return period. If the difference is large, the LSM gives larger wave heights than the EST for relatively short return periods, while the opposite happens for longer return periods. This difference between the EST and the LSM is attributed to the bounce of the relative frequency of wave height at the largest waves (or the occurrence of large wave heights off the increasing trend of wave height with return period).

Investigation of trends in extreme value wave height and wind speed

Global altimeter data spanning a period of more than 20 years is analyzed to determine whether there are measurable trends in extreme value return period estimates of wind speed and wave height. The data is subdivided into sections of 4 years duration and extreme value analysis applied to each section. The trends in values across these sections indicate that there appears to be a positive trend in 100 year return period values of wind speed but no consistent trends for 100 year return period wave height. However, the statistical uncertainty associated with estimates of the extreme value wind speed and wave heights is such that the quantitative values of trend are not reliable. Reliable values will require a longer‐duration data set.

A maximum-entropy compound distribution model for extreme wave heights of typhoon-affected sea areas

A new compound distribution model for extreme wave heights of typhoon-affected sea areas is proposed on the basis of the maximum-entropy principle. The new model is formed by nesting a discrete distribution in a continuous one, having eight parameters which can be determined in terms of observed data of typhoon occurrence-frequency and extreme wave heights by numerically solving two sets of equations derived in this paper. The model is examined by using it to predict the N-year return-period wave height at two hydrology stations in the Yellow Sea, and the predicted results are compared with those predicted by use of some other compound distribution models. Examinations and comparisons show that the model has some advantages for predicting the N-year return-period wave height in typhoon-affected sea areas.

Critical storm thresholds for significant morphological changes and damage along the Emilia-Romagna coastline, Italy

The definition of storm morphological thresholds along the coast of the Emilia-Romagna Region strictly depends on its configuration and variability. The region is located in northern Italy, facing the Adriatic Sea. The coastline is characterised by very different levels of economic development, ranging from natural zones with dunes to highly developed stretches protected by breakwaters and groynes. The Integrated Coastal Zone Management effort is mainly concentrated on preserving urban areas that generate significant income for the regional economy. Natural areas, while small in comparison to the urbanised zone, are important for environment preservation. Because of such a multiplicity of issues at stake, it was decided to produce two different thresholds: one for the morphological impact on natural sectors and another for inundation and damage to structures along urbanised zones.The “forcing” component of the threshold definition for natural areas was calculated by summing the effects of surge+tide+waves (run-up elevation) to find the Maximum Water Level (MWL) reached by the sea during one, ten and one-hundred year storm return periods. For urbanised zones, historical storm information was collected starting from the 1960s in order to identify the forcing conditions causing real damages. Each storm was classified in terms of wave height, period, direction and surge level. Morphological information were obtained from Lidar flights performed in 2003 and 2004 and from direct surveys undertaken in September 2008 and February 2009 as part of the monitoring programme for the MICORE Project.The computed MWL for each return period was then compared to beach elevations along natural areas in order to calculate the Dune Stability Factor (DSF), an index that accounts for the eroded sediment volume above the MWL during a storm. Based on analysis along 41 profile lines at a 500m spacing, it was found that the 1-in-1year return period wave height+1-in-1year return period surge are able to erode and/or overwash 2/3 of the dunes.The historical storm hydrodynamic information was used to estimate which wave and surge conditions are able to inundate at least 2/3 of the beach profiles. The MWL was again compared to beach elevations, this time along 63 anthropogenic profiles spaced 500m apart (or 1/3 of the urbanised coastline). It was found that a wave heights >=2m and surge+tide levels >=0.7m are able to flood between 18% and 36% of the built-up coast.The defined thresholds are related to the present coastal characteristics and are not “static”, meaning that they are likely to change according to future evolution of the coastline. They are very important because they can be used as thresholds to issue warnings and alert the Civil Protection. Moreover they are the first thresholds defined for the Emilia-Romagna coastline and will be used as starting values to generate “dynamic” thresholds based on numerical model predictions of morphological change for a given wave and surge level.

A new approach to estimating the T-year return-period wave height

The paper introduces a new approach to estimating the T-year return-period wave height (TRPW), i.e. the wave height expected to occur in T-year, from two sets of observed extreme data and on the basis of the maximum entropy principle. The main points of the approach are as follows. 1) A maximum entropy probability density function (PDF) for the extreme wave height H is derived from a Euler equation subject to some necessary and rational constraints. 2) The parameters in the function are expressed in terms of the mth moment of H. 3) This PDF is convenient to theoretical and practical applications as it is simple and its four parameters are easy to be determined from observed extreme data. An example is given for estimating the TRPW in 50 and 100 years by the present approach and by some currently used methods using observed data at two hydrographic stations. The comparison of the estimated results shows that the present approach is quite similar to the Pearson-III and Gumbel methods.

The wave climate of Liverpool Bay—observations and modelling

Directional wave measurements have been made in Liverpool Bay by means of wave buoys and acoustic instruments within the footprint of a phased-array high frequency (HF) radar system, which measures currents and waves. Several years of data have now been collected and are supplemented by an 11-year wave model hindcast. Wave parameters have been derived from the various instruments and compared: the directional waverider buoy is taken to provide the ground truth, confirming the good observations obtained from the ADCP; the HF radar wave data have a positive bias, while the model data have a negative bias. The variation of wave climate over various time-scales from seasonal and inter-annual to inter-decadal is examined. Significant wave–current interactions may occur in this area of shallow water and high tidal range and the measurements provide a good test of coupled hydrodynamic-wave models. The waves are mainly fetch-limited: largest events are due to depressions, which track across the UK from SW, generating westerly and WNW winds in the right rear quadrant. Hence, the future extreme wave events will be closely related to future North Atlantic storm tracks. Projections of 50-year return period wave heights differ between different instruments and model datasets. The future wave climate of Liverpool Bay is not expected to change much from the present day; although a slight increase in the severity of the most extreme events is projected, the frequency of extreme wind and wave events in general is slightly reduced. There is evidence for variability on decadal time-scales, with some correlation with the North Atlantic oscillation.

Estimating return period wave heights and wind speeds using a seasonal point process model

A method of extreme value analysis is described which incorporates a model reflecting the seasonality of the environment. A point process model is employed with the arrival of storms described as a Poisson process and a generalised Pareto distribution to model the magnitude of the storm. Separate point process models are constructed for each season and then aggregated to provide a basis for estimating the return values. The construction of separate models, including the use of seasonal thresholds, ensures that more appropriate models are fitted to each season's data. The method also reflects the completeness of the environmental record, avoiding the bias that can result from missing data. The potential benefits of the approach include greater accuracy, robustness to missing data and the provision of seasonal return values for mobile systems deployed on a temporary basis. The method is demonstrated in estimating the N year significant wave heights and wind speeds in the northern North Sea.

Hindcast estimates of extreme wave conditions in the Gulf of Maine

The Gulf of Maine is a region lacking in wave data that can be used for engineering and research purposes. Extreme wave statistics for this area are therefore computed in this paper by numerical hindcasting. A representative sample of twenty-two strong extratropical northeast storms from the period 1942–1976 was selected, and wave heights were computed with a hybrid parametric wave model. The highest wave height at each point in the Gulf of Maine model grid for each storm was used to calculate 50 and 100-year return period wave heights. It is concluded that as a first-order estimate, any major engineering effort in the Gulf of Maine will have to reckon with significant wave heights as high as 13 metres for a 1% chance of occurrence. These results agree extremely well with other estimates based on shipboard observations.

Statistics of Hurricane Waves in the Gulf of Mexico

This paper reports the results of an extensive study of hurricane-generated waves in the Gulf of Mexico. The study includes hindcasting of historical hurricanes and statistical interpretation of the hindcast wave data to determine maximum wave heights throughout the OCS of the central. and western Gulf of Mexico. Introduction The maximum wave height that reasonably can be expected to affect a structure during its lifetime is one of the more critical factors influencing the design of an offshore structure. By definition, such a wave height is a rare occurrence. The estimation of future occurrences of such waves must reflect, and indeed be derived from, the past history of storm-wave occurrences. Long-term past history of storm-wave occurrences. Long-term historical data bases are required to estimate these rare occurrences with meaningful reliability. Thus, estimating rare future occurrences poses two basic problems:developing a sufficiently long-term historical data base andinterpreting the historical data base to provide reliable estimates of future rare occurrences. The first problem can be solved effectively with hindcasting models. Hindcasting models can be developed and calibrated with contemporary data. These models then are applied with historical storm meteorological data to "re-create" an historical storm-wave data base. In this manner, the need for a long-term historical data base is satisfied by meteorological data.This paper emphasizes the solution of the second problem, which can be stated more concisely: Given an problem, which can be stated more concisely: Given an historical storm-wave data base, what is the most appropriate method for determining the cumulative probability distribution function for the largest waves probability distribution function for the largest waves that will affect a site in tY years? From that distribution function, a variety of wave statistics useful in design studies (e.g., expected maximum wave height in tY years or return-period wave heights) can be determined.This paper describes a study of hurricane-generated waves along the central and western OCS of the Gulf of Mexico. A hurricane climatology characterizing the geographical distribution, wave-generating capability, and frequency of severe hurricanes was derived from historical data. Based on this climatology, a model for estimating the cumulative probability distribution function for the largest wave in tY years from historical wave data was developed. The historical wave data base was generated by hindcasting the more severe historical hurricanes that occurred between 1900–74. Finally, the model was applied with the hindcast data and sample results are presented. Hindcasting Historical Hurricanes The historical wave data base required for this study was developed by hindcasting severe historical hurricanes. The hindcast model used has been described before and will be discussed only briefly here. Hindcast Model The hurricane hindcast model actually consists of two models - a wind-field model and a wave model. The wind-field model is based on a fundamental theoretical description of the relationship between the atmospheric pressure field and winds within a hurricane. The pressure pressure field and winds within a hurricane. The pressure field is described from historical meteorological data. JPT P. 632

Extrapolation of Historical Storm Data for Estimating Design-Wave Heights

Abstract An improved method is presented for selecting offshore structure design waves by extrapolating historical storm data to obtain extreme value statistics. The method permits flexibility in choice of distribution functions through use of computerized procedures, estimates extrapolated wave-height procedures, estimates extrapolated wave-height uncertainty due to small sample size, and includes criteria for judging whether or not given wave-height values can be represented by one or more of the distributions implemented in the method. The relevance of uncertainty to selection of design-wave heights is discussed and illustrated. Introduction The problem of selecting design-wave heights for offshore platforms has many facets, ranging from the development of oceanographic data to the selection of the prudent level of engineering risk for a particular installation. This paper deals only with part of the problem; it describes an improved method for using the small available amount of wave-height information to estimate the extreme value statistics and associated uncertainties for the large storm waves that have a very low probability of occurrence. probability of occurrence. Hindcast wave-height information for design-wave studies usually covers a period of historical record that is shorter than the return period selected for acceptable engineering risk. Return periods commonly used for selection design waves are 100 years or more, but good meteorological data, on Which the calculated wave heights are based, can rarely be obtained for periods covering more than 50 to 60 years. As a consequence, extrapolations to longer return periods are necessary. Present methods for making the extrapolation employ probablistic models through the use of special probability graph papers on which a family of distribution functions plot as straight lines. The wave heights are plotted vs their "plotting-position" return period, and a straight line fitted to the plotted data is extended beyond the data to estimate extreme wave heights for return periods of interest. The methods are described in periods of interest. The methods are described in numerous technical papers and books; Refs. 1 through 5 are examples.