• Journal of IKEEE
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• v.23 no.2
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• pp.743-746
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• 2019

In this paper we proposed a new ocean radiation automatic monitoring system. The proposed system has the following characteristics: First, using NaI + PVT mixed detectors, the response speed is fast and precision analysis is possible. Second, the application of temperature compensation algorithm to scintillator-type sensors does not require additional cooling devices and enables stable operation in the changing ocean environment. Third, since cooling system is not needed, electricity consumption is low, and electricity can be supplied reliably by utilizing solar energy, which can be installed at the observation deck of ocean environment. Fourth, using GPS and wireless communications, accurate location information and real-time data transmission function for measurement areas enables immediate warning response in the event of nuclear accidents such as those involving neighboring countries. The results tested by the authorized testing agency to assess the performance of the proposed system were measured in the range of $5{\mu}Sv/h$ to 15mSv/h, which is the highest level in the world, and the accuracy was determined to be ${\pm}8.1%$, making normal operation below the international standard ${\pm}15%$. The internal environmental grade (waterproof) was achieved, and the rate of variation was measured within 5% at operating temperature of $-20^{\circ}C$ to $50^{\circ}C$ and stability was verified. Since the measured value change rate was measured within 10% after the vibration test, it was confirmed that there will be no change in the measured value due to vibration in the ocean environment caused by waves.

• Journal of the Korean earth science society
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• v.39 no.2
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• pp.139-153
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• 2018

The sea surface wind field has long been obtained from satellite scatterometers or passive microwave radiometers. However, the importance of satellite altimeter-derived wind speed has seldom been addressed because of the outstanding capability of the scatterometers. Satellite altimeter requires the accurate wind speed data, measured simultaneously with sea surface height observations, to enhance the accuracy of sea surface height through the correction of sea state bias. This study validates the wind speeds from the satellite altimeters (GFO, Jason-1, Envisat, Jason-2, Cryosat-2, SARAL) and analyzes characteristics of errors. In total, 1504 matchup points were produced using the wind speed data of Ieodo Ocean Research Station (IORS) and of Korea Meteorological Administration (KMA) buoys at Marado and Oeyeondo stations for 10 years from December 2007 to May 2016. The altimeter wind speed showed a root mean square error (RMSE) of about $1.59m\;s^{-1}$ and a negative bias of $-0.35m\;s^{-1}$ with respect to the in-situ wind speed. Altimeter wind speeds showed characteristic biases that they were higher (lower) than in-situ wind speeds at low (high) wind speed ranges. Some tendency was found that the difference between the maximum and minimum value gradually increased with distance from the buoy stations. For the improvement of the accuracy of altimeter wind speed, an equation for correction was derived based on the characteristics of errors. In addition, the significance of altimeter wind speed on the estimation of sea surface height was addressed by presenting the effect of the corrected wind speeds on the sea state bias values of Jason-1.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.20 no.3
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• pp.119-130
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• 2015

Impacts of Argo temperature assimilation on the analysis fields in the East Sea is investigated by using DAESROM, the East Sea Regional Ocean Model with a 3-dimensional variational assimilation module (Kim et al., 2009). Namely, we produced analysis fields in 2009, in which temperature profiles, sea surface temperature (SST) and sea surface height (SSH) anomaly were assimilated (Exp. AllDa) and carried out additional experiment by withdrawing Argo temperature data (Exp. NoArgo). When comparing both experimental results using assimilated temperature profiles, Root Mean Square Error (RMSE) of the Exp. AllDa is generally lower than the Exp. NoArgo. In particular, the Argo impacts are large in the subsurface layer, showing the RMSE difference of about $0.5^{\circ}C$. Based on the observations of 14 surface drifters, Argo impacts on the current and temperature fields in the surface layer are investigated. In general, surface currents along the drifter positions are improved in the Exp. AllDa, and large RMSE differences (about 2.0~6.0 cm/s) between both experiments are found in drifters which observed longer period in the southern region where Argo density was high. On the other hand, Argo impacts on the SST fields are negligible, and it is considered that SST assimilation with 1-day interval has dominant effects. Similar to the difference of surface current fields between both experiments, SSH fields also reveal significant difference in the southern East Sea, for example the southwestern Yamato Basin where anticyclonic circulation develops. The comparison of SSH fields implies that SSH assimilation does not correct the SSH difference caused by withdrawing Argo data. Thus Argo assimilation has an important role to reproduce meso-scale circulation features in the East Sea.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.12 no.4
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• pp.251-261
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• 2007

The wind-wave interaction around the Kyung-gi Bay, Korea, was studied using the observed data from ocean buoy at DeuckJeuck-Do from Jan. to Dec., 2005, and from waverider data at KeuckYeulBee-Do on Mar. 19-26 and May 23-28, 2005. Wind-driven surface waves and wave-driven wind speed decrease were estimated from the ocean buoy data, and the characteristics of wave spectrum response were also investigated from the waverider data for the wave developing and calm stages of sea surface, including the time series of spectrum pattern change, frequency trend of the maximum energy level and spectrum slope for the equilibrium state range. The wind speed difference between before and after considering the wave effect was about $2ms^{-1}$ (wind stress ${\sim}0.1Nm^{-2}$) for the wind speed range $5-10ms^{-1}$ and about $3ms^{-1}$ (wind stress ${\sim}0.4Nm^{-2}$) for the wind speed range $10-15ms^{-1}$. Correlation coefficient between wind and wave height was increased from 0.71 to 0.75 after the wave effect considered on the observed wind speed. When surface waves were generated by wind, the initial waves were short waves about 4-5 sec in period and become in gradual longer period waves about 9-10 sec. For the developed wave, the frequency of maximum energy was showed a constant value taking 6-7 hours to reach at the state. The spectrum slope for the equilibrium state range varied with an amplitude in the initial stage of wave developing, however it finally became a constant value 4.11. Linear correlation between the frictional velocity and wave spectrum for each frequency showed a trend of higher correlation coefficient at the frequency of the maximum energy level. In average, the correlation coefficients were 0.80 and 0.82 for the frequencies 0.30 Hz and 0.35 Hz, respectively.

• Journal of Navigation and Port Research
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• v.46 no.6
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• pp.517-524
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• 2022

This paper analyzes wave measurement using X-band navigation (ship) radar, changes in radar signal due to snowfall and precipitation, and factors that obstruct wave measurement. Data obtained from the radar installed at Sokcho Beach were used, and data from the Korea Meteorological Administration and the Korea Hydrographic and Oceanographic Agency were used for the meteorological data needed for comparative verification. Data from the Korea Meteorological Administration are measured at Sokcho Meteorological Observatory, which is about 7km away from the radar, and data from the Korea Hydrographic and Oceanographic Agency are measured at a buoy about 3km away from the radar. To this point, changes in radar signals due to rainfall or snowfall have been transmitted empirically, and there is no case of an analysis comparing the results to actual weather data. Therefore, in this paper, precipitation, snowfall data, CCTV, and radar signals from the Korea Meteorological Administration were comprehensively analyzed in time series. As a result, it was confirmed that the wave height measured by the radar according to snowfall and rainfall was reduced compared to the actual wave height, and a decrease in the radar signal strength according to the distance was also confirmed. This paper is meaningful in that it comprehensively analyzes the decrease in the signal strength of radar according to snowfall and rainfall.

• Ocean and Polar Research
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• v.30 no.3
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• pp.361-372
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• 2008

A satellite tracked drifter experiment was conducted to observe thermal structure and surface circulation in the northeastern East China Sea. For this experiment, four ADOS buoys, assembled with surface float and thermister chain, were deployed on August 2007 in southern Jeju-do, where the Kuroshio Branch Current is separated from the main stream. Thermal structure in the upper layer of the northeastern East China Sea was successfully observed during the following $1{\sim}3$ months. Strong thermo-haline front in a northeast-southwest direction was observed. In the frontal zone, warm and saline Kuroshio origin water intermixes with fresher coastal water and flows toward the Korean Strait. Typhoon Nari, which passed over the East China Sea 20 days after commencement of study, caused distinct signals in the thermal structure and trajectory of buoys. During the typhoon, surface temperature abruptly dropped to about $4^{\circ}C$, while the thermocline formed at $30{\sim}50$ m depth vanished due to strong vertical mixing. Internal inertial oscillation occurred several days after the typhoon. The fortuitous occurrence of typhoon Nari showed that ADOS buoys can provide useful and accurate air-sea interaction data during typhoons.

• Korean Journal of Remote Sensing
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• v.34 no.2_1
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• pp.213-225
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• 2018

In order to access the accuracy of the gridded daily Advanced Scatterometer (hereafter DASCAT) ocean surface wind data in the surrounding of Korea, the DASCAT was compared with the wind data from buoys. In addition, the reanalysis data for wind at 10 m provided by European Centre for Medium-Range Weather Forecasts (ECMWF, hereafter ECMWF), National Centers for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR, hereafter NCEP), Modern Era Retrospective-analysis for Research and Applications-2 (MERRA-2, hereafter MERRA) were compared and analyzed. As a result, the RMSE of DASCAT for the actual wind speed is about 3 m/s. The zonal components of wind of buoys and the DASCAT have strong correlation more than 0.8 and the meridional components of wind them have lower correlation than that of zonal wind and are the lowest in the Yellow Sea (r=0.7). When the actual wind speed is below 10 m/s, the EMCWF has the highest accuracy, followed by DASCAT, MERRA, and NCEP. However, under the wind speed more than 10 m/s, DASCAT shows the highest accuracy. In the nature of error according to the wind direction, when the zonal wind is strong, all dataset has the error of more than $70^{\circ}$ on the average. On the other hand, the RMSE of wind direction was recorded $50^{\circ}$ under the strong meridional winds. ECMWF shows the highest accuracy in these results. The RMSE of the wind speed according to the wind direction varied depending on the actual wind direction. Especially, MERRA has the highest RMSE under the westerly and southerly wind condition, while the NCEP has the highest RMSE under the easterly and northerly wind condition.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.32 no.4
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• pp.273-283
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• 2020

Numerical simulations of the storm surge and waves induced by the Typhoon Bolaven incident on the west sea of Korea in 2012 are performed using the JMA-MSM weather field provided by the Japan Meteorological Agency, and the calculated surge heights are compared with the time history observed at harbours along the various coasts of Korea. For the waves occurring coincidentally with the storm surges the calculated significant wave heights are compared with the data measured using the wave buoys operated by the Korea Hydrographic and Oceanographic Agency and the Korea Meteorological Administration. Additional simulations are also performed based on the pressure and wind fields obtained using the best track information provided by the Joint Typhoon Warning Center, and the calculated results are compared and analyzed. The waves and storm surges calculated using JMA-MSM wether field agree well with the observations because of the better reflection of the topography and the pre-background weather field. On the other hand, the calculated results based on the weather fields produced using the JTWC best track information show some limitations of the general trend of the variations of wave and surge heights. Based on the results of this study it is found that the reliable weather fields are essential for the accurate simulation of storm surges and waves.

• Journal of Korean Society of Disaster and Security
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• v.16 no.4
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• pp.19-31
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• 2023

According to the climate change scenarios, the intensity of typhoons, a major factor in Korea's natural disaster, is expected to increase. The increase in typhoon intensity leads to a rise in wave heights, which is likely to cause large-scale disasters in coastal regions with high populations and building density for dwelling, industry, and tourism. This study, therefore, analyzed observation data of the Donghae ocean data buoy and conducted a numerical model simulation for wave estimations for the typhoon MAYSAK (202009) period, which showed the maximum significant wave height. The boundary conditions for wave simulations were a JMA-MSM wind field and a wind field applying the typhoon central pressure reduction rate in the SSP5-8.5 climate change scenario. As a result of the wave simulations, the wave height in front of the breakwater at Sokcho port was increased by 15.27% from 4.06 m to 4.68 m in the SSP5-8.5 scenario. Furthermore, the return period at the location of 147-2 grid point of deep-sea design wave was calculated to increase at least twice, it is necessary to improve the deep-sea design wave of return period of 50-year, which is prescriptively applied when designing coastal structures.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.33 no.6
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• pp.265-274
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• 2021

Outlier detection research in ocean data has traditionally been performed using statistical and distance-based machine learning algorithms. Recently, AI-based methods have received a lot of attention and so-called supervised learning methods that require classification information for data are mainly used. This supervised learning method requires a lot of time and costs because classification information (label) must be manually designated for all data required for learning. In this study, an autoencoder based on unsupervised learning was applied as an outlier detection to overcome this problem. For the experiment, two experiments were designed: one is univariate learning, in which only SST data was used among the observation data of Deokjeok Island and the other is multivariate learning, in which SST, air temperature, wind direction, wind speed, air pressure, and humidity were used. Period of data is 25 years from 1996 to 2020, and a pre-processing considering the characteristics of ocean data was applied to the data. An outlier detection of actual SST data was tried with a learned univariate and multivariate autoencoder. We tried to detect outliers in real SST data using trained univariate and multivariate autoencoders. To compare model performance, various outlier detection methods were applied to synthetic data with artificially inserted errors. As a result of quantitatively evaluating the performance of these methods, the multivariate/univariate accuracy was about 96%/91%, respectively, indicating that the multivariate autoencoder had better outlier detection performance. Outlier detection using an unsupervised learning-based autoencoder is expected to be used in various ways in that it can reduce subjective classification errors and cost and time required for data labeling.