• Journal of Korean Society of Coastal and Ocean Engineers
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• v.34 no.1
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• pp.11-18
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• 2022

In order to improve the accuracy of particle tracking prediction techniques near the Korean Strait, this study compared and analyzed a particle tracking model based on a seawater flow numerical model and a machine learning based on a particle tracking model using field observation data. The data used in the study were the surface drifter buoy movement trajectory data observed in the Korea Strait, prediction data by machine learning (linear regression, decision tree) using the tide and wind data from three observation stations (Gageo Island, Geoje Island, Gyoboncho), and prediciton data by numerical models (ROMS, MOHID). The above three data were compared through three error evaluation methods (Correlation Coefficient (CC), Root Mean Square Errors (RMSE), and Normalized Cumulative Lagrangian Separation (NCLS)). As a final result, the decision tree model had the best prediction accuracy in CC and RMSE, and the MOHID model had the best prediction results in NCLS.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.7
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• pp.1003-1010
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• 2013

In this paper, TCP/IP based Machine-to-Machine (M2M) communication uses CDMA/GSM network for data communication. This communication method is widely used by offshore moored buoy for data transmission back to the system server. Due to weather and signal coverage, the TCP/IP M2M communication often experiences transmission failure and causing data losses in the server. Data losses are undesired especially for meteorological and oceanographic analysis. This paper discusses a software approach to minimize M2M data losses by handling transmission failure and re-attempt which meant to transmit the data for recovery. This implementation was tested for its performance on a meteorological buoy placed offshore.

• Journal of Environmental Science International
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• v.17 no.4
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• pp.461-468
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• 2008

Competitive power of pelagic fishery in Korea has been weakened by the domestic and international problems such as wage increase and exclusive economic zone. To make it worse, fishing fleet spends more than 80% of fishing time on searching fishing grounds. Real-time information on oceanographic data, temperature in particular, are likely to contribute to raise efficiency of fishing. However, available data obtained by satellite remote sensing, fixed buoy and drifting buoy, limited to sea surface or fixed positions. ARGO (Array for Real-time Geostrophic Oceanography), an international program, has delivered vertical profiles of temperature and salinity in the upper 2000m of the world ocean every 10 days using freely moving floats. We have developed real-time oceanographic information system for pelagic fishery based on the Argo data which has the contents of vertical profile, horizontal distribution and vertical section of temperature around fishing grounds and searched data can be download unrestrictedly. Comparison of skipjack catch with sea surface temperature and depth of $20^{\circ}C$ derived from Argo data in the West Equatorial Pacific revealed that Argo data are able to help fishing fleet to find fishing grounds and to increase catch.

• Proceedings of the KSRS Conference
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• v.1
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• pp.146-149
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• 2006

Marine surface winds observed by two microwave sensors, SeaWinds and Advanced Microwave Scanning Radiometer (AMSR), on the Advanced Earth Observing Satellite-II (ADEOS-II) are evaluated by comparison with off-shore moored buoy observations. The wind speed and direction observed by SeaWinds are in good agreement with buoy data with root-mean-squared (rms) differences of approximately 1 m $s^{-1}$ and $20^{\circ}$, respectively. No systematic biases depending on wind speed or cross-track wind vector cell location are discernible. The effects of oceanographic and atmospheric environments on the scatterometry are negligible. The wind speed observed by AMSR also exhibited reasonable agreement with the buoy data in general with rms difference of 1.2 m $s^{-1}$. Systematic bias which was observed in earlier versions of the AMSR winds has been removed by algorithm refinements. Intercomparison of wind speeds globally observed by SeaWinds and AMSR on the same orbits also shows good agreements. Global wind speed histograms of the SeaWinds data and European Centre for Medium-range Weather Forecasts (ECMWF) analyses agree precisely with each other, while that of the AMSR wind shows slight deviation from them.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.34 no.3
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• pp.72-81
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• 2022

Positions of five drifting buoys deployed on August 2020 near southwestern area of Jeju Island and numerically predicted velocities were used to develop five Artificial Intelligence-based models (AI models) for the prediction of particle tracks. Five AI models consisted of three machine learning models (Extra Trees, LightGBM, and Support Vector Machine) and two deep learning models (DNN and RBFN). To evaluate the prediction accuracy for six models, the predicted positions from five AI models and one numerical model were compared with the observed positions from five drifting buoys. Three skills (MAE, RMSE, and NCLS) for the five buoys and their averaged values were calculated. DNN model showed the best prediction accuracy in MAE, RMSE, and NCLS.

• Ocean and Polar Research
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• v.32 no.3
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• pp.213-228
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• 2010

In late 2010, the Korea Hydrographic and Oceanographic Administration proposed a national monitoring project involving the deployment of 8 realtime ocean data buoys. The area occupied by the buoy-array, located south of the Ieodo Ocean Research Station, can be regarded as a kind of gateway to Korean waters with respect to warm currents and the shipping industry. The acronym for the project, KOGA (Korea Ocean Gate Array) was derived from this aspect. To ensure the success of the project, international cooperation with the neighboring countries of China and Japan is highly desirable. Once KOGA is successfully launched and the moored buoys start to produce data, the data will be applied to various areas such as data assimilation for operational oceanography, circulation dynamics, biogeochemical studies, satellite observations, and air-sea interactions. The aim of this paper is to provide suggestions for KOGA planning and applications.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.9 no.3
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• pp.111-118
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• 2004

An ocean buoy was deployed 10 km off Donghae city, Korea at a depth of 130 m to measure meteorological (air pressure, air temperature, wind speed, wind gust, wind direction, relative humidity) and oceanographic data (water properties and currents in the whole column) in real-time. The buoy recorded a maximum wind gust of 25 m/s (10 minutes' average speed of 20 m/s) and a minimum air pressure of 980 hPa when the eye of typhoon Maemi passed by near the Uljin city, Korea at 03:00 on 13 September 2003. The wave height reached maximum of 9 m with the significant wave height of 4 m at 04:00 (1 hour after the passage of Maemi). The currents measured near the surface reached up to about 100 cm/s at 13:00 (10 hours after the passage of Maemi). The mixed layer (high temperature and low salinity) thickness, which was accompanied by strong southward current, gradually increased from 20 m to 40 m during the 10 hours. A simple two layer model for the response to an impulsive alongshore wind over an uniformly sloping bottom developed by Csanady (1984) showed reasonable estimates of alongshore and offshore currents and interface displacement for the condition of typhoon Maemi at the buoy position (x=8.15 km) during the 10 hours.

• Journal of Korea Water Resources Association
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• v.46 no.5
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• pp.477-490
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• 2013

A rip-current warning index function, which is estimated from the likelihood of rip current quantified based on numerical simulations under various sea environments and is varied according to real-time buoy-observations, was studied to help protect against rip current accidents at Haeundae beach. For the quantification, the definition of likelihood of rip current, which proposed by Choi et al. (2011, 2012b), was employed and estimated based on Boussinesq modelling. The distribution of likelihood of rip current was evaluated by using various simulations according to scenarios established based on physical quantities(i.e., wave parameters) of buoy-observations. To index the likelihood of rip current, empirical functions were derived based on the distribution and adjusted to observational environments. In this study, the observations from June to September in 2011 at Haeundae beach were applied to the rip-current index functions, and its applications into the real events found based on CCTV images were presented and investigated. In addition, limitations and improvements of the rip-current index function were discussed.

• Journal of the Korean earth science society
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• v.39 no.5
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• pp.436-457
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• 2018

In this study, we apply a three-dimensional circulation model, MOHID (MOdelo $HIDrodin{\hat{a}}mico$), and reproduce oceanic variation around the East Asian seas including Korea in 2016. Simulation results are verified by using objective analysis fields (EN4, ARMOR3D, AVISO, and SIO products) and in-situ observation data (serial oceanographic and buoy data). Verification results show that general characteristics of the water temperature, sea level anomaly, surface velocity, and mixed layer depths simulated by MOHID are similar with those of the objective analysis fields in the East Asian seas. Especially, when buoy data in the coastal areas are compared, correlation coefficients of sea surface temperature and sea level anomaly are both over 0.8 and normalized standard deviations are between 0.85 and 1.15, respectively. However, it is analyzed that additional improvement would be necessary in the representation of thermocline structure in the East Sea and strong stratification phenomena in the Yellow and South Sea in summer.

• Ocean Science Journal
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• v.42 no.4
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• pp.211-222
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• 2007

We compare insolation results calculated from two well-known empirical formulas (Socket and Beaudry's SB73 formula and the original Smithsonian (SMS) formula) and a radiative transfer model using input data predicted from meteorological weather-forecast models, and review the accuracy of each method. Comparison of annual mean daily irradiance values for clear-sky conditions between the two formulas shows that, relative to the SMS, the SB73 underestimates spring values by 9 W $m^{-2}$ in the northern Adriatic Sea, although overall there is a good agreement between the annual results calculated with the two formulas. We also elucidate the effect on SMS of changing the 'Sun-Earth distance factor (f)', a parameter which is commonly assumed to be constant in the oceanographic context. Results show that the mean daily solar radiation for clear-sky conditions in the northern Adriatic Sea can be reduced as much as 12 W $m^{-2}$ during summer due to a decrease in the f value. Lastly, surface irradiance values calculated from a simple radiative transfer model (GM02) for clear-sky conditions are compared to those from SB73 and SMS. Comparison with iu situ data in the northern Adriatic Sea shows that the GM02 estimate gives more realistic surface irradiance values than SMS, particularly during summer. Additionally, irradiance values calculated by GM02 using the buoy meteorological fields and ECMWF (The European Centre for Medium Range Weather Forecasts) meteorological data show the suitability of the ECMWF data usage. Through tests of GM02 sensitivity to key regional meteorological factors, we explore the main factors contributing significantly to a reduction in summertime solar irradiance in the Adriatic Sea.