• Journal of Power System Engineering
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• v.13 no.2
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• pp.63-70
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• 2009

This paper discusses the influence on long-tenn predictions of the ship response in ocean by using the Global Wave Statistics data, GWS, and wave information from the remote sensing satellites. GWS's standard scatter diagrams of significant wave height and zero-crossing wave period are suggested to be corrected to a round number of 0.01/1000 fitted with a statistical analytic model of the conditional lognormal distribution for zero-crossing wave period. The GEOSAT satellite data are utilized which presented by I. R. Young and G. J. Holland (1996, named as GEOSAT data). At first, qualities of this data are investigated, and statistical characteristic trends are studied by means of applying known probability distribution functions. The wave height data of GEOSAT are compared to the data observed onboard merchant ships, the data observed by measure instrument installed on the ocean-going container ship and so on. To execute a long-tenn prediction of ship response, joint probability functions between wave height and wave period are introduced, therefore long-term statistical predictions are executed by using the functions.

• Journal of Ocean Engineering and Technology
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• v.32 no.2
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• pp.123-130
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• 2018

The present study investigated the validity of an equilibrium shoreline empirical formula for real phenomena. Among three types of equilibrium shoreline formulas, Hsu's parabolic type static formula was employed, which is well-known and the most practical for shoreline estimation after coastal or harbor structure construction. The wave data observed at Maengbang beach and the CERC formula on longshore sediment transport were used in the present investigation. A comparison study was only conducted for the case of a shoreline change after the construction of a groyne. Reasonable agreement was seen between the observed wave data and the data obtained under a wave angle spreading function S = 3.5. However, significant changes were observed when S increased. Thus, careful application is required when using Hsu's formula.

• Journal of Ocean Engineering and Technology
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• v.22 no.6
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• pp.13-19
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• 2008

Abnormally large swells that appeared on the coast of the East Sea in October in 2005 and 2006 were simulated using SWAN model to examine the accuracy of the model for future forecasting Seawind data calculated based on the weather chart ant bottom topography were used for input data, and the model was operated more than 20 days before the observed swells to avoid the problems from the cold start of the model. The comparisons with observed wind and wave data were unsatisfactory and neededmore improvement in terms of swell component in the wave model as well as the quality of seawind data. The satellite wind and wave data can be good candidates for future comparison of the wave model results in the East Sea.

• Journal of Environmental Science International
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• v.32 no.11
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• pp.841-852
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• 2023

In this study, the significant wave height and wave period of a specially designed observation system that connected two drifting buoys to an ocean data buoy was observed for 23 days from February 7 to 29, 2020, and the results were compared and analyzed. The results indicated that, in comparison to the ocean data buoy, the drifting buoy exhibited greater variability in significant wave height over shorter time intervals. The wave period of the ocean data buoy also appeared longer than that of the drifting buoy. The greater the observed significant wave height and wave period from both the ocean data and drifting buoys, the more pronounced the differences between the two observation instruments become. Moreover, the study revealed that the disparity in observation methods between the ocean data and drifting buoys did not significantly affect the significant wave height characteristics, as long as the period remained unchanged for up to half of the observation time.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.30 no.1
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• pp.16-30
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• 1997

Application of digital filter to the wave analysis is studied using the observed data by wave gauge. Sea wave data obtained from wave gauge always include long wave frequency components. In order to estimate the sea wave parameters, we must re-analyzed wave data by using a digital filter and the concept of mean sea level correction method. By the wave by wave analysis and spectral methods, sea wave parameters on the basis of wave data obtained by the conventional method and digital filter are compared. The best-fitted design filter determined by the necessary conditions of frequency responses, can be obtained by calculating various transfer functions. Thus, to get the best the digital filter design, both Butterworth filter and Savitzky-Golay filter of digital filter are used in the frequency and time domain, respectively. Three cases of observation wave data are calculated by applying digital filter. The components of different frequency bands in the surf zone are coexisted in three cases. The wave data for wind wave components is computed using the digital filter the surf zone and off-surf zone, and based on the filtered data, wave parameters are calculated by the spectral analysis and wave by wave analysis methods, respectively. As a results, when sea wave data observed by wave gauge are analyzed, the Savitzky-Golay method is recommended which can well appear cut-off frequency by experimental choosing filter length in the time domain. The better mean sea level correction method is the Butterworth filter in the frequency domain.

• Korean Journal of Remote Sensing
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• v.28 no.1
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• pp.95-100
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• 2012

Big swell is often generated offshore and damages the coasts after travelling long distance. In order to prevent coastal damages, wave measurements should be performed offshore as well as coastal waters around Korea. However, in-situ wave measurements are difficult because of high expense of instruments and high risk of operation. Satellite wave measurements using altimeter make it possible to get wave information from the sea difficult to execute field measurements such as the center of the East Sea or exclusive territorial waters. In order to use wave information from the satellite altimeter, it is important to verify altimeter wave data with in-situ data. This paper examines significant wave height data observed by ENVISAT altimeter by comparing wave data observed at Ieodo station.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.28 no.4
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• pp.212-221
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• 2016

In this study, characteristics of swell-like high waves in the East Sea were analyzed using observed wave data and predicted meteorological data from the National Oceanic and Atmospheric Administration (NOAA). And, the wave prediction system using the data from the NOAA has been established. Furthermore, the applicability of the system has been verified by comparing the predicted results with the corresponding observed data. For some case, there were two times of wave height increase and the second increase occurred in a calm weather condition on the coast which might cause casualties. The direction of wave energy propagation was estimated from observed wave data in February, 2008. Through comparison between the direction of wave energy propagation and the meteorological data, it turns out that the second increase of waves is originated from the seas between Russia and Japan which is far from the East Sea.

• Journal of Coastal Disaster Prevention
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• v.4 no.1
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• pp.7-19
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• 2017

In this study, waves and currents observed by acoustic AWAC, VECTOR and Aquadopp Profiler in Anmok coastal waters were analysed to account for the variability of wave and current and to understand the mechanism of sediment transport generated by wave-induced current in the surf-zone. The monthly variation of wave and residual currents were analysed and processed with long-term observed AWAC data at station W1, located at the water depth of about 18m measured during from February 2015 to September 2016. Wave-induced currents were also analysed with intensive field measurements such as wave, current, suspended sediment, and bathymetry data observed at the surf-zone during in winter and summer. The statistical result of wave data shows that high waves coming from NNE and NE in winter (DEC-FEB) are dominant due to strong winds from NE. But in the other season waves coming from NE and ENE are prevalent due to the seasonal winds from E and SE. The residual currents with southeastern direction parallel to the shoreline are dominant throughout a year except in winter showing in opposite direction. The speed of ebb-dominant southeastern residual currents decreasing from surface to the bottom is strong in summer and fall but weak in winter and spring. By analysing wave-induced current, we found that cross-shore current were generated by swell waves mainly in winter with incoming wave direction about $45^{\circ}$ normal to the shoreline. Depending on the direction of incoming waves, longshore currents in the surf-zone were separated to southeastern and northwestern flows in winter and summer respectively. The variation of observed currents near crescentic bars in the surf-zone shows different direction of longshore and cross-shore currents depending on incoming waves implying to the reason of beach erosion generating the beach cusp and sandbar migration during high waves at Anmok.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.26 no.3
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• pp.149-159
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• 2014

In this study, we develop an algorithm to predict swell-like high waves on the east coast of Korea using the directional wave gauge which was installed near Sokcho. Using the numerical wave model SWAN, we estimate wave data in open sea from the wave data collected by using the directional wave gauge. Then, using the wave ray method and SWAN model with the open-sea wave data as offshore boundary conditions, we predict the swell-like high waves at several major points on the east coast of Korea. We verify the prediction methods with the SWAN and wave ray methods by comparing predicted data against measured one at Wangdolcho. We can improve the prediction of the swell-like high waves in the east sea of Korea using both the real-time wave measurement system and the present prediction algorithm.

• Journal of Ocean Engineering and Technology
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• v.38 no.3
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• pp.103-114
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• 2024

Remote sensing wave observation data are crucial when analyzing ocean waves, the main external force of coastal disasters. Nevertheless, it has limitations in accuracy when used in low-wind environments. Therefore, this study collected the raw data from MIROS Wave and Current Radar (MWR) and wave radar at the Ieodo Ocean Research Station (IORS) and applied the optimal filter by combining filters provided by MIROS software. The data were validated by a comparison with South Jeju ocean buoy data. The results showed it maintained accuracy for significant wave height, but errors were observed in significant wave periods and extreme waves. Hence, this study used an artificial neural network (ANN) to improve these errors. The ANN was generalized by separating the data into training and test datasets through stratified sampling, and the optimal model structure was derived by adjusting the hyperparameters. The application of ANN effectively improved the accuracy in significant wave periods and high wave conditions. Consequently, this study reproduced past wave data by enhancing the reliability of the MWR, contributing to understanding wave generation and propagation in storm conditions, and improving the accuracy of wave prediction. On the other hand, errors persisted under high wave conditions because of wave shadow effects, necessitating more data collection and future research.