Sea Wave Height Research Articles

Investigation of Electromagnetic Scattering Mechanisms from Dynamic Oil Spill–Covered Sea Surface

The electromagnetic (EM) scattering mechanism of dynamic oil spill–covered sea surface area is studied in this manuscript. Utilizing the theory of oil film diffusion combined with oil spill volume, a three–dimensional (3D) geometric model of dynamic oil spill–covered sea surface area is established. The changes of the geometric structure and statistical characteristics of the sea surface area under the influence of the oil film are also analyzed. The thinner the oil spill thickness, the more sensitive it is to the sea surface slope and wave height. The facet-based hybrid model and the multilayer dielectric scattering method are combined to measure the EM scattering on the sea surface when covered by dynamic oil spills. In addition, the hydrodynamic and tilt effect are discussed. The EM scattering mechanism of the dynamic oil spill–covered sea surface area is revealed, and the tilt modulation is greater than the hydrodynamic effect in the dynamic process of an oil spill. It provides an important reference for the remote sensing monitoring of oil.

Simulating a Sea Wave Power Plant for Malaysia

The demand for electricity in Malaysia is growing yearly. Renewable energy from the sea waves is one of the solutions to solve the energy crisis in Malaysia. Malaysia has a long coastline of 4,675 kilometres. Therefore, simulating a sea waves power plant for Malaysia is an interest of this study. This research is aim to identify the suitable locations for installing sea waves power plants in Malaysia and to simulate the total power generated by the sea waves power plant by using Hybrid Optimization Model for Multiple Energy Resources (HOMER). HOMER is a power optimization software and it is used to simulate and analyze the sea waves power plant in the generation system. The sea wave height, the period, and the water depth are collected from the selected regions. From the results, it shows that the sea waves peak periods are between 3 s and 5 s whereas the wave heights are between 0.5 m and 1 m respectively. The HOMER and analytical results show that the total rate of electrical power connected to the grid for Malaysia is 1408.81 MWh per year and 1408.89 MWh per year, respectively.

Analysis of the effect of seed growth (Rhizophora apiculata) on the distance of land from the beach in of Pulau Sembilan Pangkalan Susu District Langkat Regency

Mangrove is a renewable resource that provides services related to the environment, such as abrasion protection, seawater control of incursion, reduction of sea wave height and speed, cleaning of water contaminants, among others, important to support living beings. Its objectives include to study and evaluate the impact of planting distance from the beach which is useful for increasing growth for mangrove ecosystem type Rhizophora apiculata and this study based on a complete randomized design (RAL) with treatment distance (J) consisting of 5 treatments (a) P0 (planting distance from the beach 41 meters), (b) P1 (planting distance from the beach 42 meters), (c) P2 (planting distance from the beach 43 meters), (d) P3 (distance from the beach 44 meters) (e) P4 (planting distance from the beach 45 meters). The percentage of plant growth is 100%. Observational Data on the measurement of height, diameter, leaf count, leaf size, and leaf area, that the treatment at planting distance can increase the growth of seedlings R. apiculata. Based on the results of the study the effect of planting distance on R. apiculata obtained in the treatment of P2 (planting distance from the beach 43 m) a seedling height value that was highest growth with a value of 198.0 cm or average 33.0 cm. The highest value of plant diameter obtained from the treatment of P3 (spacing 44 m) with a value of 7.74 mm or average 1.29 mm . The highest added value was found in treatment P1 with a value total number of 39.2 strands or average 6.5 strands. The increase in leaf area is 50.9 cm or average 8.4 cm which is found in the P2 treatment.

On the Non-Gaussianity of Sea Surface Elevations

The sea surface elevations are generally stated as non-Gaussian processes in the current literature, being considered Gaussian for short periods of relatively low wave heights. The objective here is to study the evolution of the distribution of the sea surface elevation from Gaussian to non-Gaussian as the period of time in which the associated time series is recorded increases. To do this, an empirical study based on the measurements of the buoys in the US coast downloaded at a casual day is performed. This study results in rejecting the null hypothesis of Gaussianity in below 25% of the cases for short periods of time and in over 95% of the cases for long periods of time. The analysis pursued relates to a recent one by the author in which the heights of sea waves are proved to be non-Gaussian. It is similar in that the Gaussianity of the process is studied as a whole and not just of its one-dimensional marginal, as it is common in the literature. It differs, however, in that the analysis of the sea surface elevations is harder from a statistical point of view, as the one-dimensional marginals can be Gaussian, which is observed throughout the study and in that a longitudinal study is performed here.

Impact of the ENSO phenomenon on wave variability in the Pacific Ocean for wind sea and swell waves

Using wave data from 1960 to 1990 from the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis ERA-40 dataset and the ERA-5 reanalysis dataset (1990–2018), this paper presents a comprehensive study on the spatial and temporal variability of wind sea wave height (Hw), swell wave height (Hsw) and mixed significant wave height (Hs) in the Pacific during the warm (El Niño) and cold (La Niña) ENSO phases. The main findings show that During DJF, the Hsw is dominated by strong winds and large waves from extratropical cyclones in the North Pacific, especially from 1960 to 1990. However, from 1990–2018 these maximum values extend into the subtropical crest of the Pacific Ocean and the southeast trade winds increase during La Niña. The annual cycle of Hw, Hsw and Hs for specific points located from the west center toward the east center along the equatorial Pacific for the analyzed decades show a strong transition in the locations of the maximum and minimum values during the year. In this sense, the eastern point is more highly influenced by the swell systems that flow from the northwest and southwest of the southern hemisphere associated with the intensification of winds during the occurrence of La Niña. It is therefore not possible to determine a single period of maximum and minimum values. During the decades of 1990–2018, the difference in swell wave height during La Niña compared to El Niño increased throughout the year compared to 1960–1990. During the 1960–1990 period, the maximum values were detected in JJA for both El Niño and La Niña in an area that extends from Perú and ends toward the eastern center of the Colombian Pacific Basin.

Multiparametric sea state fields from synthetic aperture radar for maritime situational awareness

This paper introduces a method for estimating a series of sea state parameters from satellite-borne synthetic aperture radar (SAR). The method was realized in a near real time (NRT) application which allows for the processing of data from different satellites and modes. The algorithm estimates the total significant wave height Hs, dominant and secondary swell and windsea wave heights, first, and second moment wave periods, the mean wave period and the period of wind sea. The algorithm was applied to the Sentinel-1 (S1) C-band Interferometric Wide Swath Mode (IW), Extra Wide (EW) and Wave Mode (WV) Level-1 (L1) products and also extended to X-band TerraSAR-X (TS-X) StripMap (SM) products. The scenes are processed in raster and result in continuous sea state fields, with the exception of S1 WV, where averaged values for sea state parameters for along-orbit imagettes of 20 km × 20 km are presented.The developed empirical algorithm consists of two parts: a first CWAVE_EX (extended CWAVE) part, based on a linear regression approach, and a subsequent machine learning part using the support vector machine (SVM) technique. A series of new data preparation steps (i.e. filtering, denoising) and new features estimated from SAR images are also introduced. The algorithm was tuned and validated using two independent global wave model hindcasts, WaveWatch-3 and MFWAM as well as National Data Buoy Center (NDBC) measurements. The achieved root mean squared errors (RMSE) for CWAVE_EX for the total Hs are 0.60 m for low-resolution modes S1 IW (10 m pixel) and EW (40 m pixel) and 0.35 m for S1 WV and TS-X SM (pixel spacing ca.1–4 m) in comparison to model predictions. The RMSEs of the retrieved wave periods are in the range of 0.45–0.90 s for all of the satellites and models considered. Similarly, the dominant and secondary swell, and wind sea wave height RMSEs are in the range of 0.35–0.80 m. The SVM postprocessing improves the accuracy of the initial results of CWAVE_EX for Hs and reaches an RMSE of 0.25 m for S1 WV. Comparisons to 64 NDBC buoys, collocated at distances shorter than 50 km to S1 WV imagettes worldwide, result in an RMSE of 0.41 m. All results and the methods presented are novel in terms of the accuracy achieved, combining the classical approach with machine learning techniques, and performing an automatic NRT processing of multiparametric sea state fields from L1 data with automatic switching for different satellites and modes.The complete archive of S1 WV L1 Single Look Complex products from December 2014 until February 2021 was processed to create a sea state parameter database and validated using model hindcast and buoy measurements. The derived parameters are available to the public within the scope of the European Space Agency's Climate Change Initiative.

Seamless Projections of Global Storm Surge and Ocean Waves Under a Warming Climate

AbstractFor coastal adaptation purposes, it is important to estimate the climate related changes in extreme sea levels due to storm surges and ocean waves, in addition to mean sea level rise. This study provides the first consistent and continuous estimation of projected changes in global storm surges and ocean waves from the past to the warmer future, based on an extremely high resolution global climate model. The spatial pattern in the trend of annual maximum sea surface heights and wave heights is predominantly driven by changes in tropical cyclone (TC) frequency. In the western North Pacific, future TC frequencies are projected to decrease, and the annual maximum sea surface heights and wave heights show decreasing trends (−20 cm/century and −200 cm/century). Although highly intense tropical cyclones are enhanced in the warmer climate, highly extreme storm surges and wave heights do not necessarily increase due to the large natural variability.

Coastal observation of sea surface tide and wave height using opportunity signal from Beidou GEO satellites: analysis and evaluation

Coastal observation of sea surface tide and wave height using opportunity signal from Beidou GEO satellites: analysis and evaluation

Design auto trajectory of passenger ship in variation of sea condition in line Ketapang - Gilimanuk of Bali strait, Indonesia

The fleet of ferry ships crossing in the Bali Strait between Ketapang - Gilimanuk is relatively old, where when the waves are quite large and the current is strong enough the ships cannot go directly to Ketapang or vice versa. In order for the ship to reach its destination, it needs the right trajectory based on sea conditions. An automatic control system algorithm is proposed to perform an auto trajectory system. New trajectory is created base on the sea conditions. The auto trajectory system consists of steering and speed control system. The study was done by computer simulation and using of Matlab software. Simulations were carried out for various conditions of sea current speed of 3-7 knots and waves with in height of 1-1.5 meters. The auto trajectory system used of adaptive fuzzy control system to determine the proportional - integral and - derivatives (PID) gain controller. The rules in fuzzy control use the Sugeno type. The performances of control to meet IMO standards and produced 5 trajectory models for various current and wave heights, in both of the direction from the north (Java Sea) and from the south (Australian sea). The fuzzy control can keep the ship on its trajectory with the largest error of 3.93 meters when the sea current is 7 knots from the south and the sea wave height is 1.5 meters.

CLTS-Net: A More Accurate and Universal Method for the Long-Term Prediction of Significant Wave Height

Significant wave height (SWH) prediction plays an important role in marine engineering areas such as fishery, exploration, power generation, and ocean transportation. For long-term forecasting of a specific location, classical numerical model wave height forecasting methods often require detailed climatic data and incur considerable calculation costs, which are often impractical in emergencies. In addition, how to capture and use the dynamic correlation between multiple variables is also a major research challenge for multivariate SWH prediction. To explore a new method for predicting SWH, this paper proposes a deep neural network model for multivariate time series SWH prediction—namely, CLTS-Net. In this study, the sea surface wind and wave height in the ERA5 dataset of the relevant points P1, P2, and P3 from 2011 to 2018 were used as input information to train the model and evaluate the model’s SWH prediction performance. The results show that the correlation coefficients (R) of CLTS-Net are 0.99 and 0.99, respectively, in the 24 h and 48 h SWH forecasts at point P1 along the coast. Compared with the current mainstream artificial intelligence-based SWH solutions, it is much higher than ANN (0.79, 0.70), RNN (0.82, 0.83), LSTM (0.93, 0.91), and Bi-LSTM (0.95, 0.94). Point P3 is located in the deep sea. In the 24 h and 48 h SWH forecasts, the R of CLTS-Net is 0.97 and 0.98, respectively, which are much higher than ANN (0.71, 0.72), RNN (0.85, 0.78), LSTM (0.85, 0.78), and Bi-LSTM (0.93, 0.93). Especially in the 72 h SWH forecast, when other methods have too large errors and have lost their practical application value, the R of CLTS-Net at P1, P2, and P3 can still reach 0.81, 0.71, and 0.98. The results also show that CLTS-Net can capture the short-term and long-term dependencies of data, so as to accurately predict long-term SWH, and has wide applicability in different sea areas.

On the Non-Gaussianity of the Height of Sea Waves

The objective of this paper is to prove that the sea wave height is not a Gaussian process. This is contrary to the common belief, as the height of a sea wave is generally considered a Gaussian process. With this aim in mind, an empirical study of the buoys along the US coast at a random day is pursued. The analysis differs from those in the literature in that we study the Gaussianity of the process as a whole and not just of its one-dimensional marginal. This is done by making use of random projections and a variety of tests that are powerful against different types of alternatives. The study has resulted in a rejection of the Gaussianity in over 96% of the studied cases.

The Impact of Tropical Cyclone Seroja to The Rainfall and Sea Wave Height in East Nusa Tenggara

Natural events following the activity of the Tropical Cyclone Seroja in April 2021 are investigated. During its active phase, Tropical Cyclone Seroja generated extreme rainfall events in some sub-provinces of East Nusa Tenggara (NTT): Ngada, Alor, Belu, Rote Ndao on 4 April, 2021, Kupang on 4 to 5 April, 2021, East Sumba on 4 to 6 April, 2021. Moreover, these extreme rainfall events triggered flood in Alor, East Flores, Lembata, The City of Kupang, Kupang, East Sumba, Malaka, Belu, and North Central Timor. The maximum sea wave height of the Indian Ocean at the Southern part of NTT was also increasing, from 4 meters on 1 to 2 April, 2021 up to 6 meters on 3 April, 2021, and rose to higher than 7 meters on 4 to 6 April, 2021. On 7 to 9 April, 2021, the sea wave height declined as the Tropical Cyclone Seroja moved to the Southwest of NTT.

Investigation of Atmospheric Conditions Associated with a Storm Surge in the South-West of Iran

Severe thunderstorms are often accompanied by strong vertical air currents, temporary wind gusts, and heavy rainfall. The development of this atmospheric phenomenon over tropical shallow water zones, such as bays, can lead to intensification of atmospheric disturbances and produce a small-scale storm surge. Here, the storm surge that occurred on 19 March 2017 in the Persian Gulf coastal area has been investigated. Air temperature, precipitation, mean sea level pressure, wave height, wind direction, wind speed, geopotential height, zonal components, meridional winds, vertical velocity, relative humidity, and specific humidity obtained from the European Centre for Medium-Range Weather Forecasts (ECMWF) and Global Forecast System (FNL) were used to implement the Weather Research and Forecasting (WRF) model. The results showed that the main cause of the storm surge was the occurrence of a supercell thunderstorm over the Persian Gulf. The formation of this destructive phenomenon resulted from a downburst under Cumulonimbus cloud and high-velocity air subsidence, after collision with the sea surface coinciding with the high tide. This caused a severe, yet temporary, gust, which in turn caused the creation of the four waves of 3.1 m height along the coast of Bandar Dayyer.

Kajian Energi Gelombang Laut Di Daerah Abrasi Serangai, Bengkulu Utara Melalui Pengamatan Tinggi Gelombang Laut

<p class="AbstractText"><span lang="EN-AU">The Serangai area, Batik Nau District, North Bengkulu has the highest average abrasion speed of 20 m/year. The abrasion could cause the coastal area to erode the coastline till several tens of meters. The purpose of this study was to determine the height of the ocean waves and to determine the energy of the ocean waves that has the potential to accelerate the abrasion process in the Serangai area. The research was carried out on November 5-7, 2018 in the Serangai beach area at a depth of 5 m using SBE 26 Plus Seagauge Wave equipment. The results showed that the observed wave height was between 0.8-1.6 m with a significant wave height (Hs) of 1.38 m. In addition, the wave period ranges from 5-11 s with a significant wave period (Ts) of 8.2 s. The result also shows that the maximum wave height of 1.6 m occurred on November 7, 2018 with maximum wave energy of 1800 J/m<sup>2</sup>. This result can perhaps accelerate the abrasion process in the Serangai area. It can also be seen that the wave height in the Serangai region is higher than in several other areas in Indonesia. However, it is necessary to continue observing the wave height to see the seasonal variations in sea wave height in Serangai area.</span></p>

Measuring the Height of Sea Waves by the Method of Radar Sounding with Polarization-Modulated Signals

Measuring the Height of Sea Waves by the Method of Radar Sounding with Polarization-Modulated Signals

Analysis on statistical uncertainties of wave loads and structural fatigue reliability for a semi-submersible platform

The statistical uncertainties of wave loads have large proportions in the structural fatigue strength analysis of offshore platforms. To investigate the uncertainties of wave loads during predicting fatigue loads, the assessing methods and formulas are proposed involving the wave spectrum, sea wave height, wave loading transfer function, zero-crossing period, possibility of sea state occurrence and wave direction; meanwhile, the model test of the wave loads is carried out in a see-keeping basin for studying the uncertainty of the wave loading transfer function. The corrected formulas of the significant wave height and mean zero-crossing period are statistically regressed by calculating the sea states in the Northwest Pacific and South China Sea. Furthermore, the influence factors of the sea states of difference seasons are analysed, and the distribution law of the wave direction of the wave loads and fatigue life of a semi-submersible platform are investigated. Finally, the fatigue reliability index of typical structures for a semi-submersible platform is assessed on the basis of uncertainties of wave loads and the other uncertainties of structural factors.

Effects of large-scale atmospheric circulation on the Baltic Sea wave climate: application of the EOF method on multi-mission satellite altimetry data

Wave heights in the Baltic Sea in the period 1992–2015 have mainly increased in the sea’s western parts. The linear trends in the winter wave heights exhibit a prominent meridional pattern. Using the technique of Empirical Orthogonal Functions (EOF) applied to multi-mission satellite altimetry data, we explain a large part of this increase with the Scandinavia pattern, North Atlantic Oscillation and Arctic Oscillation climatic indices. The winter trends show a statistically significant negative correlation (correlation coefficient –0.47 ± 0.19) with the Scandinavia pattern and a positive correlation with the North Atlantic Oscillation (0.31 ± 0.22) and Arctic Oscillation (0.42 ± 0.20). The meridional pattern is associated with more dominant north-westerly and westerly winds driven by the Scandinavia pattern and North Atlantic Oscillation, respectively. All three climatic indices show a statistically significant time-variable correlation with Baltic Sea wave heights during the winter season. When the Scandinavia pattern’s influence is strong, the North Atlantic and Arctic Oscillation effects are low and vice versa. The results are backed up by simulations using synthetic data that demonstrate that the percentage of variance explained using EOF analysis from the satellite-derived wave measurements is directly related to the percentage of noise in the data and that the retrieved spatial patterns are insensitive to the level of noise.

Prediction of the height and period of sea waves in the coastal waters of Meulaboh, Aceh Province, Indonesia

This research examines the prediction of sea waves in the coastal waters of Meulaboh. The sea wave prediction are based on the 2015-2019 monsoons in the coastal waters of Meulaboh. The method used is an empirical equation that consist of wave parameters, i.e., significant wave height Hmo and peak period Tp . The sea wave prediction generate an average of the height and period of the sea waves of 0.7 m; 5 s in the Southwest direction. Based on the prediction, it shows that the sea waves in Meulaboh coastal waters are influenced by the Southwest wind that blows towards the coast from the Indian Ocean.

An EEMD-BiLSTM Algorithm Integrated with Boruta Random Forest Optimiser for Significant Wave Height Forecasting along Coastal Areas of Queensland, Australia

Using advanced deep learning (DL) algorithms for forecasting significant wave height of coastal sea waves over a relatively short period can generate important information on its impact and behaviour. This is vital for prior planning and decision making for events such as search and rescue and wave surges along the coastal environment. Short-term 24 h forecasting could provide adequate time for relevant groups to take precautionary action. This study uses features of ocean waves such as zero up crossing wave period (Tz), peak energy wave period (Tp), sea surface temperature (SST) and significant lags for significant wave height (Hs) forecasting. The dataset was collected from 2014 to 2019 at 30 min intervals along the coastal regions of major cities in Queensland, Australia. The novelty of this study is the development and application of a highly accurate hybrid Boruta random forest (BRF)–ensemble empirical mode decomposition (EEMD)–bidirectional long short-term memory (BiLSTM) algorithm to predict significant wave height (Hs). The EEMD–BiLSTM model outperforms all other models with a higher Pearson’s correlation (R) value of 0.9961 (BiLSTM—0.991, EEMD-support vector regression (SVR)—0.9852, SVR—0.9801) and comparatively lower relative mean square error (RMSE) of 0.0214 (BiLSTM—0.0248, EEMD-SVR—0.043, SVR—0.0507) for Cairns and similarly a higher Pearson’s correlation (R) value of 0.9965 (BiLSTM—0.9903, EEMD–SVR—0.9953, SVR—0.9935) and comparatively lower RMSE of 0.0413 (BiLSTM—0.075, EEMD-SVR—0.0481, SVR—0.057) for Gold Coast.

Study of the influence of cempaka tropical cyclone on the height of sea waves in the South Java sea using the Delft 3D application

Tropical cyclone Cempaka entered South Java sea from 25th November 2017 until 27th November 2017 and caused strong winds and high waves. Delft 3D Modeling Simulation was used to investigate the effect of tropical cyclone Cempaka development on sea level rise in coastal areas and high waves in the South Java sea. The FNL wind data with a resolution of 0.25° × 0.25 ° and GEBCO bathymetry data with a grid resolution of 30 seconds was used as input to the Delft 3D model. The results of the study showed that there was an increase of significant wave height during the tropical cyclone Cempaka period with significant wave values from 1 to 3.5 meters on 27th November 2017. While for the value of sea level height in the coastal area showed results there was an increase during cyclone Cempaka period with anomalies values to 0.4. However, at the center of the cyclone had a low anomaly value that reached -0.2. From the results of the correlation test and RMSE test on sea level Delft 3D output obtained a correlation value of 0.85 and error 0.43 in the Sadeng, Yogyakarta. while the correlation test and RMSE test for the significant wave height parameter obtained a correlation value -0.198 and error value 0.168.