Extreme Wave Heights Research Articles

Influence of climate variability on wind‐sea and swell wave height extreme over the Indo‐Pacific Ocean

AbstractIn the Indo‐Pacific Ocean (IPO), extreme significant wave heights (SWHs) can substantially induce coastal erosion, flooding, and devastating impacts on coastal livelihoods. This study examines the seasonal influence of the El Niño–Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), Southern Annular Mode (SAM), and Pacific North American (PNA) pattern on extreme wind‐wave parameters. The climatic extremes are calculated utilizing ERA5 reanalysis datasets from 1979 to 2019 and a nonstationary generalized extreme value distribution. Significant increases in extreme wind‐sea (Hmax) and swell SWH (HmaxSw) response to ENSO occur over the northeast North Pacific (NP) during December–February (DJF) and western NP during June–August (JJA). The PNA influence exhibits a similar pattern to ENSO during DJF yet is inactive in JJA. Hmax and HmaxSw responses to the IOD during September–November (SON) include significant increases over the western Pacific, southern Indian Ocean (IO), and southwest tropical IO, yet decreases over the central tropical IO. The HmaxSw response to the SAM is larger than that for Hmax over the southern IPO during DJF, which extends toward the eastern Pacific in March–May (MAM). Overall, extreme wind‐sea and swell parameter responses are found to be associated with sea level pressure (SLP) and SLP gradients.

Offshore renewable energy site correlated wind-wave statistics

Offshore engineering often requires estimation of extreme wind speeds and wave heights at offshore in-situ locations. This paper presents practical approach to study extreme wind speed and wave height statistics, based on available in-situ hourly wind speed and wave height maxima. The wind and wave data, studied in this paper, was obtained from numerical hind cast model, locally applied to the offshore the area that covers SEM-REV (European wind and wave energy research site) location, for the time period 2001–2010 years.To obtain accurate local wind and wave data set, accurate wave and wind measurements from in-situ monitoring tools (meteorological stations and buoys) as well as remote satellite sensing data (ENVISAT and TOPEX satellite records) were plugged into atmospheric wind and wave model.The novel bivariate correction technique based on the Average Conditional Exceedance Rate (ACER) method has been presented in brief detail. The bivariate correction method produced quite accurate extreme value predictions, efficiently utilizing available wind speeds and wave heights data set.In some practical situations it would be useful to improve accuracy of some statistical predictions, using information supplied by another synchronous highly correlated random process that has been measured for a longer time than the process of interest. In this paper the novel technique of improving correlated extreme wind speed and wave height predictions has been presented.

Assessment of the Coastal Vulnerability Index (CVI) for disaster mitigation strategies in some coastal tourism areas in Gunungkidul, Yogyakarta-Indonesia

South coastal area of Gunungkidul, Yogyakarta-Indonesia has a high tourism development due to the unique physical conditions of coastal typology. However, during the last few years, extreme wave height associated with cyclones damaged many tourist facilities there. Coastal management for ecosystem sustainability requires disaster mitigation, which one considering the aspect of vulnerability. This study aims to assess the level of coastal vulnerability according to coastal typology of Baron-Pok Tunggal section and to determine the coastal management model based on the level of vulnerability. The Coastal Vulnerability Index (CVI) is used in vulnerability assessment. The variable formulation of CVI is divided into hydrodynamic factors (mean significant wave heights, mean tide range, and mean sea level rise) and morphodynamics factors, i.e. geomorphology, coastal slope, and average width of emerged beach. The morphodynamics data were obtained through observation, direct measurements in the field by systematic sampling, extraction from aerial photographs and digital surface model (DSM). The results of modeling and predictions by several agencies are derived to obtain the hydrodynamics data. The result of this study revealed that marine deposition coast typology have a high and moderate vulnerability (twelve and eleven coastal units, respectively). Meanwhile, a low vulnerability can be found in the cliff coast or wave erosion coast typology (24 units). The convex or concave beaches tend to be more vulnerable than beaches with the straight form. The beaches of Buluk, Drini, Kosakora, Sarangan and all beaches from Krakal to Indrayanti have a high vulnerability. Geomorphological variables, significant wave height, and sea level rise have the strongest influence on vulnerability. Coastal management in the marine deposition coast typology can be carried out either in a protective manner or by accommodative approach, such as by observing changes in natural conditions due to sea level rise.

Extreme wave height detection based on the meteorological data, using hybrid NOF-ELM method

ABSTRACT The realization of accurate extreme wave height occurrence prediction is essential for offshore and onshore structures. In this paper, a new hybrid Natural Outlier Factor-Extreme Learning Machine (NOF-ELM) method is proposed to predict the extreme wave height occurrence based on the meteorological data. Four major hurricanes in the Gulf of Mexico are used to evaluate the performance of the proposed model. Moreover, the effect of metrological parameters on the occurrence of extreme wave height is investigated. The results of the ELM classifier are then compared with traditional classification techniques, including Logistic Regression, C4.5 Decision Trees, Discriminant Analysis, k-Nearest Neighbours, classic Multi-Layer Perceptron neural networks, and Support Vector Machines. The results show that the proposed method performs well in extreme wave height detection based on metrological parameters by mean accuracy higher than 99%. Furthermore, the results indicate that radial basis ELM has the best performance in extreme wave detection.

Global extreme significant wave height within the dominant directional sector

The assessment of global directional extreme significant wave height (SWH) is crucial for the ocean infrastructure, which requires the dominant directional sector to be identified. In this study, 40-year (1979–2018) global SWHs and wave directions obtained from ERA5 are employed as the initial database. To study the extreme wave, storms over the initial threshold are extracted, which show that the non-tropical cyclonic storm is stable with the direction and most directions are within the dominant directional sector. Thus, the directional extrapolation is performed based on the independent non-tropical cyclone sample. To identify the dominant directional sector, an automated method is proposed based on the circular mean sample. Benefiting from this method, global patterns of sector width and representative direction of dominant directional sector can be obtained and classified. To make sufficient use of extreme samples for reasonable extrapolation, the peak over threshold method with the generalized Pareto distribution model is employed to evaluate the global directional extreme SWHs. The spatially comparable patterns accord with the distribution of wind zones and reveal the effect of swells in low latitudes, which can be used to realize design optimization and key protection of ocean infrastructures, especially for infrastructures that are not symmetrical.

Intraseasonal variability of ocean surface wind waves in the western South Atlantic: the role of cyclones and the Pacific South American pattern

Abstract. Extratropical cyclones are known to generate extreme significant wave height (swh) values at the ocean surface in the western South Atlantic (wSA), which are highly influenced by intraseasonal scales. This work aims to investigate the importance of intraseasonal timescales (30–180 d) in the regional climatology of waves and its atmospheric forcing. The variability is explained by analyzing the storm track modulation due to westerly winds. These winds present timescales and spatial patterns compatible with the intraseasonal component of the Pacific South American (PSA) patterns. The analyses are made using ECMWF’s ERA5 from 1979 to 2019 and a database of extratropical cyclones based on the same reanalysis. Empirical orthogonal function (EOF) analyses of the 10 m zonal wind and swh are used to assess the regime of westerlies and waves in the wSA. The EOF1 of the 10 m zonal wind (u10) presented a core centered at 45∘ W and 40∘ S, while the EOF2 is represented by two cores organized into a seesaw pattern with a center between 30–40∘ S and another to the south of 40∘ S. Composites of cyclone genesis and track densities as well as swh fields were calculated based on the phases of both EOFs. In short, EOF phases presenting cores with a positive (negative) u10 anomaly provide a favorable (unfavorable) environment for cyclone genesis and track densities and, therefore, positive (negative) swh anomalies. The modulation of the cyclone tracks is significant for extreme values of the swh. The spatial patterns of the EOFs of u10 are physically and statistically consistent with 200 and 850 hPa geopotential height signals from the Pacific, indicating the importance of the remote influence of the PSA patterns over the wSA.

Climate Change Impacts on Wind Waves Generated by Major Tropical Cyclones off the Coast of New Jersey, USA

Coastal areas of State of New Jersey in the Northeastern United States are exposed to extreme wind waves generated by tropical cyclones in the Atlantic Ocean. Past studies suggest that the frequency and intensity of major hurricanes in the Atlantic basin would increase under high greenhouse gas emission scenarios. Furthermore, sea level observations have revealed that the local mean sea level along the coast of New Jersey is rising at a rate higher than that of the global sea level rise. The objective of this study is to quantify the combined influence of sea level rise (SLR) and hurricane climatology change on wave heights induced by major hurricanes off the coast of New Jersey. To this end, a coupled hydrodynamic-wave model is utilized to simulate wind waves for synthetic hurricanes generated for the climate conditions in the historical period of 1980–2000 and future period of 2080–2100 under the RCP8.5 high emission scenario. The synthetic storms are generated by a hurricane model for the climate conditions obtained from four different global climate models. The projections of future wave heights show statistically significant increases in the wave heights induced by major hurricanes. Under the combined effects of hurricane climatology change and a SLR of 1.19 m, the increase in the extreme wave heights 15% in back-bays and shallow waters of the nearshore zone and up to 10% in deeper coastal waters. It is found that SLR alone would result in a significant increase in the hurricane-induced wave heights in the present-day surf zone.

CMIP5 model evaluation for extreme ocean wave height responses to ENSO

CMIP5 model evaluation for extreme ocean wave height responses to ENSO

Wind Waves in the Mediterranean Sea: An ERA5 Reanalysis Wind-Based Climatology

A climatology of the wind waves in the Mediterranean Sea is presented. The climate patterns, their spatio-temporal variability and change are based on a 40-year (1980–2019) wave hindcast, obtained by combining the ERA5 reanalysis wind forcing with the state-of-the-art WAVEWATCH III spectral wave model and verified against satellite altimetry. Results are presented for the typical (50th percentile) and extreme (99th percentile) significant wave height and, for the first time at the regional Mediterranean Sea scale, for the typical and extreme expected maximum individual wave height of sea states. The climate variability of wind waves is evaluated at seasonal scale by proposing and adopting a definition of seasons for the Mediterranean Sea states that is based on the satellite altimetry wave observations of stormy (winter) and calm (summer) months. The results, initially presented for the four seasons and then for winter and summer only, show the regions of the basin where largest waves occur and those with the largest temporal variability. A possible relationship with the atmospheric parameter anomalies and with teleconnection patterns (through climate indices) that motivates such variability is investigated, with results suggesting that the Scandinavian index variability is the most correlated to the Mediterranean Sea wind-wave variability, especially for typical winter sea states. Finally, a trend analysis shows that the Mediterranean Sea typical and extreme significant and maximum individual wave heights are decreasing during summer and increasing during winter.

Predictability of Coastal Extreme Wave Heights Based on a Nonstationary Hierarchical Bayesian Model: The Role of the Sea Surface Temperature

Kim, Y.-T.; Uranchimeg, S.; Park, M.H., and Kwon, H.-H., 2021. Predictability of coastal extreme wave heights based on a nonstationary hierarchical Bayesian model: The role of the sea surface temperature. In: Lee, J.L.; Suh, K.-S.; Lee, B.; Shin, S., and Lee, J. (eds.), Crisis and Integrated Management for Coastal and Marine Safety. Journal of Coastal Research, Special Issue No. 114, pp. 191–195. Coconut Creek (Florida), ISSN 0749-0208. The increasing frequency of extreme wave heights has been observed in many parts of the world due to recent global warming. Especially, the variability of extreme wave heights in the summer season has increased during the last three decades over the coast of South Korea that is partially attributable to the increase of the climate variability, leading to the changes in frequency and intensity of the extreme wave heights. Further, coastal areas are particularly vulnerable to the increased climate variability, and the associated risk can be exacerbated by the rapid coastal development over South Korea. Most of the extreme wave heights in South Korea are largely caused by a typhoon during the summer season. Recent studies revealed that the typhoon frequency and intensity in the Asian monsoon region are modulated by Sea Surface Temperature (SST) during the summer season from May to November. Traditional frequency analysis methods do not consider the year to year shifts in wave heights risk distributions that are attributed to changes in climate variability that affect the causal structure of coastal inundation risk. In this perspective, a climate-informed nonstationary frequency analysis model is proposed to predict the extreme wave heights and explore the role of the SST in a Bayesian regression framework. The parameters of the nonstationary frequency model are obtained using a Markov Chain Monte Carlo algorithm. The proposed model shows strong potential for predicting the extreme wave heights by linking large-scale climate patterns, providing motivation for developing dynamic coastal flood risk management strategies.

Dynamics and stratigraphy of a tidal sand ridge in the Bristol Channel (Nash Sands banner bank) from repeated high‐resolution multibeam echo‐sounder surveys

AbstractRepeated multibeam echo‐sounder surveys can provide information on developing stratigraphy over large areas and during periods when environmental conditions are known. In this study, analysis encompasses 13 time‐separated multibeam echo‐sounder surveys between 2002 and 2010 of a tidal sand ridge in a macrotidal estuary: Nash Sands, a banner bank in the Bristol Channel (UK). Over the surveyed period, Nash Sands was S‐shaped in plan‐view, with twoen échelonsegments separated by a channel (swatchway). Migration of these inflections along the ridge led to deposition of clinoforms up to 5° to 7° steep and 12 to 14 m tall. The clinoforms downlapped onto their substrates or onto cross‐sets formed by dunes migrating clockwise around the lower flanks of the ridge. Clinoform topsets were removed or truncated by repeated erosion and/or dune migrations over the ridge crest and replaced with packages of near‐horizontal laterally discontinuous irregular beds. Flank dune crests were oriented obliquely to nearly perpendicularly to the clinoforms in all three sets, so the clinoforms developed by oblique−lateral accretion locally. Although one area had strongly eroded in the prior decade during elevated wave conditions, the 2002 to 2010 stratigraphic development revealed a different relationship with extreme wave heights; Nash Sands generally accumulated sand during times of more extreme waves and lost sand during more quiescent conditions. Using also single‐beam survey data from 1991 to 2002 to study the ridge morphology over 19 years to 2010, the swatchway was absent in 1991 to 1992 and progressively developed as the ridge sinuosity became more accentuated. Dunes found migrating north‐west through the swatchway are potential evidence of a current caused by tidal height differences across the ridge during ebb conditions. The study illustrates how repeated sonar measurements reveal the processes and timescales that lead to the deposition of stratigraphic units.

Estimation of extreme wave heights and wind speeds in the South China Sea

Extreme events have significant impacts on the coastal and offshore regions. In the present paper, the return values of significant wave height and wind speed are estimated based on three different models namely generalized extreme value distribution, generalized Pareto distribution and polynomial approximation to acquire a universal and trustworthy model estimate. Here, six sites in the South China Sea with diverse geographical characteristics are considered to perform the extreme value analysis and the datasets used in the experiments were derived from the ERA-Interim reanalysis. Then the advantages and shortcomings of three different methods are discussed and analyzed in detail. The polynomial approximation method is analyzed and compared with the other methods, and it is found that this new method predominantly resolves the drawbacks encountered by the other typical extreme value estimation methods and it is suitable for estimating the return values in the South China Sea.

Climate regime shifts and biodiversity redistribution in the Bay of Biscay

Global ocean warming, wave extreme events, and accelerating sea-level rise are challenges that coastal communities must address to anticipate damages in coming decades. The objective of this study is to undertake a time-series analysis of climate change (CC) indicators within the Bay of Biscay, including the Basque coast. We used an integrated and flexible methodology, based on Generalized Additive Mixed Models, to detect trends on 19 indicators (including marine physics, chemistry, atmosphere, hydrology, geomorphology, biodiversity, and commercial species). The results of 87 long-term time series analysed (~512,000 observations), in the last four decades, indicate four groups of climate regime shifts: 1) A gradual shift associated with CC starting in the 1980s, with a warming of the sea surface down to 100 m depth in the bay (0.10-0.25 °C per decade), increase in air temperature and insolation. This warming may have impacted on benthic community redistribution in the Basque coast, favouring warm-water species relative to cold-water species. Weight at age for anchovy and sardine decreased in the last two decades. 2) Deepening of the winter mixed layer depth in the south-eastern bay that probably led to increases in nutrients, surface oxygen, and chlorophyll concentration. Current increases on chlorophyll and zooplankton (i.e., copepods) biomass are contrary to those expected under CC scenarios in the region. 3) Sea-level rise (1.5-3.5 cm per decade since 1990s), associated with CC. 4) Increase of extreme wave height events of 16.8 cm per decade in the south-eastern bay, probably related to stormy conditions in the last decade, with impacts on beach erosion. Estimating accurate rates of sea warming, sea-level rise, extreme events, and foreseeing the future pathways of marine productivity, are key to define the best adaptation measures to minimize negative CC impacts in the region.

The performance of the copulas in estimating the joint probability of extreme waves and surges along east coasts of the mainland China

In designing coastal and nearshore structures, the joint probability of the wave heights and storm surges is essential in determining the possible highest total water level. The key elements to accurately estimate the joint probability are the appropriate sampling of the extreme values and selection of probability functions for the analysis. This study is to provide a full assessment of the performance of the different methods employed in the joint probability analysis. The bivariate extreme wave height and surge samples are analysed using 2 different probability distributions and the performance of 4 copulas, namely: Gumbel–Hougaard copula, Clayton copula, Frank copula and Galambos copula, is assessed. The possible highest total water levels for 100-year return period along the coastline of the mainland China are estimated by the joint probability method with the Gumbel–Hougaard copula. The results show that the wave heights and surges are highly correlated in the areas of dense typhoon paths. The distributions of the possible highest total water levels show a higher value in the southeast coast and lower value in the north. The results also indicate that at the locations where the sea states are energetic, the joint probability approach can improve the accuracy of design.

Changes in extreme ocean wave heights under 1.5 °C, 2 °C, and 3 °C global warming

This study inspects the global changes in seasonal extreme ocean wave heights under different levels of global warming (1.5 °C, 2 °C, and 3 °C) based on statistical wave projections derived from CMIP5 multi-model simulations. The results show robust increases in wave extremes up to 15% (∼1 m) over Southern Hemisphere high latitudes and tropical Pacific, particularly at 3 °C warming. Strong seasonality is observed, especially for the North Pacific. Under higher warming, stronger increases are identified in both amplitude and area of extreme wave heights. The change in magnitude translates into shorter return intervals of extreme wave events in a warmer world, particularly at 3 °C warming. Differences between 1.5 °C and 2 °C worlds reveal potential benefits of limiting global warming over large regions of global ocean. Strong inter-model relationships indicate that wave height increases are associated with intensified climate mode variability, particularly the Southern Annular Mode and El Niño–Southern Oscillation, in a warmer world. An important implication is the potential impact of increased wave extremes on West Antarctic ice shelves with respect to calving and associated loss of buttressing, which would facilitate sea level rise in a warmer world.

Response of extreme significant wave height to climate change in the South China Sea and northern Indian Ocean

Abstract The frequency of extreme wave events is increasing with climate change. The temporal and spatial variations of extreme wave height affect both human livelihood and the usage of ocean resources. The South China Sea and northern Indian Ocean both support coastal communities of high population density, with varied terrain structures and extreme wind and wave systems. This study focuses on the temporal and spatial variations of the extreme significant wave height in the South China Sea and northern Indian Ocean. Using nonstationary generalized extreme value analysis, trends for a 100-year return period of significant wave height were obtained for both. The most rapid increase in the 100-year return was found to be 0.015 m yr-1 in the northern South China Sea and in the Arabian Sea; however, the 100-year return significant wave height fell in the mouth of the Bay of Bengal. After analyzing the possible causes and influence factors, we found that the increase in significant wave height in the northern South China Sea was dominated by local wind-waves and similarly, the Arabian Sea was affected by swell. The NINO3.4 index shows good correlation with the significant wave height in the northern South China Sea because typhoons are related to NINO3.4 in this area. The trends of the extreme wave height in the Arabian Sea and southern Bay of Bengal have good correlations with the South Asian summer monsoon index.

Height wave modelling using spatial extreme value with max stable process (MSP) brown-resnick model

Analysis of extreme data containing spatial elements can be used the Spatial Extreme Value method, which is applied with a max-stable process approach. The data preprocessing process begins by identifying the extreme data of each location for each time period or block. This method is also called Block maxima. The data obtained from the Block Maxima process will follow the Generalized Extreme Value (GEV) distribution. GEV has three forms of distribution, namely Gumbel, Frechet and Weibull. In this study, the data will be transformed into the frechet distribution margin because the frechet has a heavy tail shape, this is required in MSP modeling. Smith model, Schlater model, and Brown Resnik model are the three main models in MSP. Brown technical model is used in this research because Brown Resnick form is a flexible ta of stationary max stable processes in Gaussian random fields. The best model is selecting based on the smallest TIC value from all combinations of Trend surface models. The selected model is then used to determine the prediction of the extreme wave height for each location with a certain time period. The location used in this study is a point where fishermen are widely used to find fish, namely Semarang, Pekalongan, and Rembang which are in Central Java Province.

Long-term spatio-temporal trends in extreme wave events in the Niger delta coastlines.

Wave climate in the marginal seas and estuaries provide baseline information, risk assessments and essential insight into coastal design, structure and engineering projects. This paper investigates the Spatio-temporal trends in extreme Significant Wave Height (SWH) in the Niger Delta coastlines. For the study domain, European Centre for Medium-Range Weather Forecasts (ECMWF) global atmospheric reanalysis ERA-Interim and wave hindcast data covering 37 years (January 1, 1980–December 31, 2016), derived from WAVEWATCH III (WW3) model were used in the analysis. The largest 99th percentile approach was used to analyze extreme SWH values. Results showed near neutral and negative trends over the region. The trends are generally insignificant for the 100-year return period. The sharp variation in extreme SWH between 1998 and 2000 resulted from a strong El Nino and La Nina phenomenon, which is associated with the weakening and strengthening of the West-African Monsoon.

Freak wave in high-order weakly nonlinear wave evolution with bottom topography change

In deep-water, quasi-resonant four-wave interaction gives rise to the occurrence probability of extreme wave height, which leads to freak wave as a natural disaster. As water wave enters shallow water, four-wave interaction becomes weak and wave shoaling makes this effect become complicated. This study conducts a Monte Carlo simulation in modified Nonlinear Schrödinger equation considering bottom topography change, and gives spatial evolution of high-order nonlinearity in wave train from statistical moment. The result indicates, slope angle plays an important role in a shallow water depth, and steep slope brings about a significant enhancement of extreme event in distribution of maximum wave height and surface elevation.

Comprehensive Wind and Wave Statistics and Extreme Values for Design and Analysis of Marine Structures in the Adriatic Sea

Wind and waves present the main causes of environmental loading on seagoing ships and offshore structures. Thus, its detailed understanding can improve the design and maintenance of these structures. Wind and wave statistical models are developed based on the WorldWaves database for the Adriatic Sea: for the entire Adriatic Sea as a whole, divided into three regions and for 39 uniformly spaced locations across the offshore Adriatic. Model parameters are fitted and presented for each case, following the conditional modelling approach, i.e., the marginal distribution of significant wave height and conditional distribution of peak period and wind speed. Extreme significant wave heights were evaluated for 20-, 50- and 100-year return periods. The presented data provide a consistent and comprehensive description of metocean (wind and wave) climate in the Adriatic Sea that can serve as input for almost all kind of analyses of ships and offshore structures.