• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.707-723
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• 2022

Although satellite-based sea surface temperature (SST) is advantageous for monitoring large areas, spatiotemporal data gaps frequently occur due to various environmental or mechanical causes. Thus, it is crucial to fill in the gaps to maximize its usability. In this study, daily SST composite fields with a resolution of 4 km were produced through a two-step machine learning approach using polar-orbiting and geostationary satellite SST data. The first step was SST reconstruction based on Data Interpolate Convolutional AutoEncoder (DINCAE) using multi-satellite-derived SST data. The second step improved the reconstructed SST targeting in situ measurements based on light gradient boosting machine (LGBM) to finally produce daily SST composite fields. The DINCAE model was validated using random masks for 50 days, whereas the LGBM model was evaluated using leave-one-year-out cross-validation (LOYOCV). The SST reconstruction accuracy was high, resulting in R² of 0.98, and a root-mean-square-error (RMSE) of 0.97℃. The accuracy increase by the second step was also high when compared to in situ measurements, resulting in an RMSE decrease of 0.21-0.29℃ and an MAE decrease of 0.17-0.24℃. The SST composite fields generated using all in situ data in this study were comparable with the existing data assimilated SST composite fields. In addition, the LGBM model in the second step greatly reduced the overfitting, which was reported as a limitation in the previous study that used random forest. The spatial distribution of the corrected SST was similar to those of existing high resolution SST composite fields, revealing that spatial details of oceanic phenomena such as fronts, eddies and SST gradients were well simulated. This research demonstrated the potential to produce high resolution seamless SST composite fields using multi-satellite data and artificial intelligence.

• Proceedings of the KSRS Conference
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• 2001.03a
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• pp.104-110
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• 2001

Ocean heat fluxes over a wide region are generally estimated by an aerodynamic bulk fromula. Though a remote sensing technique can be expected to estimated global heat flux, it is difficult to obtain air temperature and specific humidity at sea surface by a remote sensor. In this study present a new method with which to determine near-sea surface air temperature from in situ data. Also, These methods compared with other methods. A new method used a linear regression equation between sea surface temperature and air temperature of the buoys data. In this study new method is validated using observed monthly mean data at the Japan Meteorological Agency(JMA), National Data Buoy Center(NDBC) and Tropical Ocean-Global Atmosphere(TOGA)-Tropical Atmosphere Ocean(TAO) buoys. The result that bias and rmse are 0.28, 1.5$0^{\circ}C$ respectively. The correlation coefficient is 0.98. Also, to retrieve near-sea surface specific humidity(Q) from good nonlinear regression relationship between vapor pressure(Ea) of buoy data and air temperature, after obtained the third-order polynomial function, compared with that of estimated from SSM/I empirical equation by Schussel et al(1995). The result that bias and rmse are -1.42 and 1.75(g/kg).

• Journal of the Korean Society for Marine Environment & Energy
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• v.5 no.4
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• pp.41-47
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• 2002

The surface current in the region from Mara-do to mid of the Pacific has been measured by tracking the position of a buoy. The buoy was accidentally released from its original location, near Mara-do, and it has been drifting following the surface current. The tracking started on 27 December 2001 and continued until 29 June 2002. We combined the trace oi the buoy with the wind data available.

• Journal of the Korean Association of Geographic Information Studies
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• v.8 no.3
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• pp.142-149
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• 2005

To provide observed oceanography data at coastal fish and shellfish farm in the northeastern sea of the Korean peninsula on real time base, we developed real time application system for fisheries oceanography information. The system has been made up a mooring buoy system, a server for oceanography data collection, a server for archiving data and a database system, and a web server for providing fisheries oceanography information using internet. Futhermore, to support letters service on a cellular phone, we developed the communication system from mooring buoy to cell phone on real time base. The oceanography data derived from the system are water temperature speed and direction of current in surface layer middle layer and bottom layer in hour. We were able to quantify short term variation of ocean conditions within several days at shellfish farm such as a scallop sea farm using our system. To reduce damages of fish and shellfish farm from abnormal phenomena of ocean conditions such as a broken stratification of water, an occurrence of abnormal coastal cold water and warm water we will be able to move vertically and horizontally the sea farm facilities to proper conditions using real time oceanography information derive from the system.

• Korean Journal of Remote Sensing
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• v.34 no.6_3
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• pp.1383-1398
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• 2018

Sea surface wind is one of the most fundamental variables for understanding diverse marine phenomena. Although scatterometers have produced global wind field data since the early 1990's, the data has been used limitedly in oceanic applications due to it slow spatial resolution, especially at coastal regions. Synthetic Aperture Radar (SAR) is capable to produce high resolution wind field data. KOMPSAT-5 is the first Korean satellite equipped with X-band SAR instrument and is able to retrieve the sea surface wind. This study presents the validation results of sea surface wind derived from the KOMPSAT-5 backscattering coefficient data for the first time. We collected 18 KOMPSAT-5 ES mode data to produce a matchup database collocated with buoy stations. In order to calculate the accurate wind speed, we preprocessed the SAR data, including land masking, speckle noise reduction, and ship detection, and converted the in-situ wind to 10-m neutral wind as reference wind data using Liu-Katsaros-Businger (LKB) model. The sea surface winds based on XMOD2 show root-mean-square errors of about $2.41-2.74m\;s^{-1}$ depending on backscattering coefficient conversion equations. In-depth analyses on the wind speed errors derived from KOMPSAT-5 backscattering coefficient data reveal the existence of diverse potential error factors such as image quality related to range ambiguity, discrete and discontinuous distribution of incidence angle, change in marine atmospheric environment, impacts on atmospheric gravity waves, ocean wave spectrum, and internal wave.

• Journal of the Korean earth science society
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• v.22 no.1
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• pp.40-46
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• 2001

Heat exchange between the atmosphere and sea is produced using the data from two 3m discus buoy installed by KMA in 1996. The meteorological and oceanic characteristics at the Dukjukdo and Chilbaldo buoy for the period 1996 ${\sim}$ 2000 are discussed. Daily averaged sensible heat and latent heat flux at each site are estimated from bulk aerodynamic method using given data and analyzed. Quantitative analyses show SST indicates 1-year cycle like air temperature but has 1 month lag. Sea level pressure is lowest in July, humidity is higher from May to August, and wind speed has averaged value of 5 m/s and higher in autumn and winter. Sensible heat flux analyses present that strong heat loss from the sea occurs in autumn and winter and weak heat loss from atmosphere appears in spring and summer, and net sensible heat loss from the sea is found throughout the year. The ocean significantly releases latent heat into atmosphere from August to May but get a little latent heat from atmosphere in other months. Net latent heat loss from the sea is larger than net sensible heat loss except in January and February. Comparison with two sites suggests that the magnitude of heat flux and their fluctuation are generally stronger at Dukjukdo than at Chilbaldo. In case study, both sensible and latent heat flux is a little more at Chilbaldo in March 1998, but substantially stronger at Dukjukdo in November 1996.

• Journal of the Korean Society of Marine Environment & Safety
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• v.22 no.7
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• pp.869-875
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• 2016

The purpose of this study is to analyze the long-term wave characteristics and tendencies of coastal waters near Korea based on wave hind-casting modelling. Wave hind-casting modelling was performed with a wind data set from ECMWF (2001~2014), which provides data from 1979 to the present. The results of numerical modelling were verified with observed data collected using wave buoys installed by the Korea Meteorological Administration (KMA) and Korea Hydrographic and Oceanographic Agency (KHOA) in offshore waters. The results agreed well with observations from buoy stations, especially during event periods such as typhoons. The quantitative RMSE value was 0.5 m, which was significant. Consequently, the results of a wave tendency analysis for 14 years (2001~2014) showed an increased appearance ratio for waves of more than 2 m in height at all regional domains. The mean appearance ratio was 0.082 % per year, which implies that coastal waves have been increasing continuously. This coastal wave tendency analysis data can be used to evaluate coastal vulnerability due to recent climate change and the design of coastal erosion prevention structures.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.10a
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• pp.597-601
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• 2000

Sea fog/stratus is very difficult to detect because of the characteristics of air-sea interaction and locality, and the scantiness of the observed data from the oceans such as ships or ocean buoys. The aim of our study develops new algorism for sea fog detection by using Geostational Meteorological Satellite-5(CMS-5) and suggests the technics of its continuous detection.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2019.11a
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• pp.153-154
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• 2019

본 연구에서는 일본 기상청(JMA)에서 제공하는 JMA-MSM (Meso-Scale Model) 바람장을 SWAN 모델에 입력자료로 적용하여 파랑전파를 모의하였다. 영역은 심해역·중간역·연안역으로 설정하였다. 산출된 모델링의 결과는 관측자료와 비교·검증하여 모델 구축에 대한 신뢰성을 확보하였다. 그리고 연안역에서 SWAN모델의 파랑스펙트럼정보를 입력조건으로 하는 SWASH모델의 영역을 구축하여 두 모델간 파랑전파양상을 비교하였다. SWAN(phase-averaged) 모델과 SWASH(phase-resolving) 모델은 지배방정식의 차이에 따라 파랑의 위상처리 방식 등의 차이가 있다. 이로 인한 연안역에서의 파랑전파양상의 차이를 비교하였다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.4B
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• pp.243-251
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• 2012

To investigate the characteristics of rip current occurring at Haeundae beach, observations obtained from a buoy and a CCTV were analyzed and numerical experiments were conducted. During observed rip-current events, the CCTV images showed that a couple of wave-trains, which are close to regular waves with slightly different directions, propagated to the beach, and wavelet analyses of data from the buoy showed very narrow-banded spectra with a peak frequency. From the evidences, it was inferred that a known mechanism of generating rip current due to the nodal line area of honeycomb-patterned wave crest was one of the significant factors of rip current occurrences of Haeundae beach. The mechanism has been explained by the following: When two wave-trains with slightly different directions propagate to a beach, wave crests of the incident wave-trains form honeycomb pattern due to nonlinear interaction. The nodal lines of honeycomb pattern are developed in the cross-shore direction. And longshore currents flow toward the nodal line area which has very low wave energy. Consequently their mass flux is expelled through the area toward the sea direction. To confirm the generation, numerical experiments were performed using a nonlinear Boussinesq equation model. In the cases with two incident wave-trains with slightly different directions and with a monochromatic wave propagating over a submerged shoal, it was seen that the honeycomb pattern of wave crests was well developed, and thus rip currents were evolved along the nodal lines.