• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.10 no.1
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• pp.69-78
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• 2005

ARCO and TAO data which supply three dimensional global ocean information are assimilated to the background field from a general circulation model, MOM3. Using a variational Analysis using Filter (VAF), which is a spatial variational filter designed to reduce computational time and space efficiently and economically, observed ARGO and TAO data are assimilated to the OGCM-generated background sea temperature for the generation of initial condition of the model. For the assessment of the assimilation impact, a comparative experiment has been done by integrating the model from different intial conditions: one from ARGO-, TAO-data assimilated initial condition and the other from background state without assimilation. The assimilated analysis field not only depicts major oceanic features more realistically but also reduces several systematic model bias that appear in every current OGCMs experiments. From the 10-month of model integrations with and without assimilated initial conditions, it is found that the major assimilated characteristics in sea temperature appeared in the initial field remain persistently throughout the integration. Such implies that the assimilated characteristics of the reduced sea temperature bias is to last in the integration without rapid restoration to the non-assimilated OGCM integration state by dispersing mass field in the form of internal gravity waves. From our analysis, it is concluded that the data assimilation method adapted in this study to MOM3 is reasonable and applicable with dynamical consistency. The success in generating initial condition with ARGO and TAO data assimilation has significant implication upon the prediction of the long-term climate and weather using ocean-atmosphere coupled model.

• Korean Journal of Remote Sensing
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• v.33 no.3
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• pp.275-285
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• 2017

National Meteorological Satellite Center(NMSC) has produced Sea Surface Temperature (SST) using Communication, Ocean, and Meteorological Satellite(COMS) data since April 2011. In this study, we have developed a new regional COMS SST algorithm optimized within the North-West Pacific Ocean area based on the Multi-Channel SST(MCSST) method and made a composite SST using polar orbit satellites as well as the COMS data. In order to retrieve the optimized SST at Northwest Pacific, we carried out a colocation process of COMS and in-situ buoy data to make coefficients of the MCSST algorithm through the new cloud masking including contaminant pixels and quality control processes of buoy data. And then, we have estimated the composite SST through the optimal interpolation method developed by National Institute of Meteorological Science(NIMS). We used four satellites SST data including COMS, NOAA-18/19(National Oceanic and Atmospheric Administration-18/19), and GCOM-W1(Global Change Observation Mission-Water 1). As a result, the root mean square error ofthe composite SST for the period of July 2012 to June 2013 was $0.95^{\circ}C$ in comparison with in-situ buoy data.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.26 no.1
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• pp.49-61
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• 2021

The repeated shipboard measurements that have been conducted by the National Institute of Fisheries Science (NIFS) for more than a half century, provide the valuable long-term hydrographic data with high spatial-temporal resolution. However, this unprecedent dataset has been rarely used for oceanic climate sciences because of its reliability issue. In this study, temporal variability of salinity error in the NIFS data was quantified by means of extremely small variability of salinity in the deep layer of the south-western East Sea, in order to contribute to studies on long-term variability of the East Sea. The NIFS salinity errors estimated on the isothermal surfaces of 1℃ have a remarkable temporal variation, such as ~0.160 g/kg in the year of 1961~1980, ~0.060 g/kg in 1981~1994,~0.020 g/kg in 1995~2002, and ~0.010 g/kg in 2003~2014 on average, which basically represent bias error. In the recent years, even though the quality of salinity has been improved, there still remain relatively large bias errors in salinity data presumably due to failure of salinity sensor managements, especially in 2011, 2013, and 2014. On the contrary, the salinity in the year of 2012 was very accurate and stable, whose error was estimated as about 0.001 g/kg comparable to the salinity sensor accuracy. Thus, as long as developing proper data quality control procedures and sensor management systems, I expect that the NIFS shipboard hydrographic data could have good enough quality to support various studies on ocean response to climate variabilities. Additionally, a few points to improve the current NIFS shipboard measurements were suggested in the discussion section.

• Fisheries and Aquatic Sciences
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• v.25 no.9
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• pp.473-488
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• 2022

To have a better understanding of the impact of the PETRONAS oil and gas platform on commercial fisheries activities, Universiti Malaysia Terengganu (UMT) examined two approaches which are data collection from satellite and data collection from fishermen and anglers. By profiling the anglers who utilize reefed oil and gas structures for fishing, it can determine if the design and location of the reef platforms will benefit or negatively impacts those anglers and fisherman. Furthermore, this assessment will be contributing to the knowledge regarding the value of offshore oil and gas platforms as fisheries resources. Collectively, the apparent fishing activity data included, combined with the findings in the reefing viability index will help to inform PETRONAS's future decommissioning decisions and may help determine if the design and proposed locations for future rigs-to-reefs candidates would benefit commercial fishing groups, further qualifying them as appropriate artificial reef candidates. The method applied in this study is approaching by using a data satellite known as Google's Global Fishing Watch technology, which is one of the applications to measure commercial fishing efforts around the globe. The apparent commercial fishing effort around the selected twelve PETRONAS platforms was analyzed from January 2012 to December 2018. Using the data collection from fishermen which is the total estimation of commercial fish value cost (in Malaysia ringgit, MYR [RM]) in Peninsular Malaysia Asset, Sabah Asset, and Sarawak Operation region. The data were extracted every month from 2016 to 2018 from the National Oceanic and Atmospheric Administration database. Most of the selected platforms that show a high frequency of vessels around the year are platform KP-A, platform BG-A and platform PL-B. The estimated values of commercial fishes varied between platforms, with ranged from RM 10,209.92 to RM 89,023.78. Thus, platforms with high commercial fish value are selected for reefing in-situ and will serve multi-purposes and benefit the locals as well as the country. The current study has successfully assessed the potential reefing area of the Malaysian offshore environment with greater representativeness and this paper focused on its potential as a new fishing ground.

• Korean Journal of Remote Sensing
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• v.39 no.3
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• pp.355-361
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• 2023

Temperature of the Earth's surface is a crucial physical variable in understanding weather and atmospheric dynamics and in coping with extreme heat events that have a great impact on living organismsincluding humans. Thermalsensors on satellites have been a useful meansfor acquiring surface temperature information for wide areas on the globe, and thus characterization of its estimation uncertainty is of central importance for the utilization of the data. Among various factors that affect the estimation, the uncertainty caused by the algorithm itself has not been tested for the atmospheric environment of Korean vicinity. Thisstudy derivesthe uncertainty of the single-channel algorithm under the local atmospheric and oceanic conditions by using reanalysis data and buoy temperature data collected around Korea. Atmospheric profiles were retrieved from two types of reanalysis data, the fifth generation of European Centre for Medium-Range Weather Forecasts reanalysis of the global climate and weather (ERA5) and Modern-Era Retrospective analysis for Research and Applications-2 (MERRA-2) to investigate the effect of reanalysis data. MODerate resolution atmospheric TRANsmission (MODTRAN) was used as a radiative transfer code for simulating top of atmosphere radiance and the atmospheric correction for the temperature estimation. Water temperatures used for MODTRAN simulations and uncertainty estimation for the single-channel algorithm were obtained from marine weather buoyslocated in seas around the Korean Peninsula. Experiment results showed that the uncertainty of the algorithm varies by the water vapor contents in the atmosphere and is around 0.35K in the driest atmosphere and 0.46K in overall, regardless of the reanalysis data type. The uncertainty increased roughly in a linear manner as total precipitable water increased.

• Journal of the Korean earth science society
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• v.45 no.1
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• pp.48-71
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• 2024

Typhoons are representative oceanic and atmospheric phenomena that cause interactions within the Earth's system with diverse influences. In recent decades, the typhoons have tended to strengthen due to rapidly changing climate. The 2022 revised science curriculum emphasizes the importance of teaching-learning activities using advanced science and technology to cultivate digital literacy as a citizen of the future society. Therefore, it is necessary to solve the temporal and spatial limitations of textbook illustrations and to develop effective instructional materials using global-scale big data covered in the field of earth science. In this study, according to the procedure of the PDIE (Preparation, Development, Implementation, Evaluation) model, the inquiry activity data was developed to visualize the track of the typhoon using the image data of GK-2A. In the preparatory stage, the 2015 and 2022 revised curriculum and the contents of the inquiry activities of the current textbooks were analyzed. In the development stage, inquiry activities were organized into a series of processes that can collect, process, visualize, and analyze observational data, and a GUI (Graphic User Interface)-based visualization program that can derive results with a simple operation was created. In the implementation and evaluation stage, classes were conducted with students, and classes using code and GUI programs were conducted respectively to compare the characteristics of each activity and confirm its applicability in the school field. The class materials presented in this study enable exploratory activities using actual observation data without professional programming knowledge which is expected to contribute to students' understanding and digital literacy in the field of earth science.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.4
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• pp.875-884
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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(GMS-5) and suggests the technics of its continuous detection. In this study, atmospheric synoptic patterns on sea fog day of May, 1999 are classified; cold air advection type(OOUTC, May 10, 1999) and warm air advection type(OOUTC, May 12, 1999), respectively, and we collected two case days in order to analyze variations of water vapor at Osan observation station during May 9-10, 1999.So as to detect daytime sea fog/stratus(OOUTC, May 10, 1999), composite image, visible accumulated histogram method and surface albedo method are used. The characteristic value during day showed A(min) .20% and DA < 10% when visible accumulated histogram method was applied. And the sea fog region which is detected is similar in composite image analysis and surface albedo method. Inland observation which visibility and relative humidity is beneath 1Km and 80%, respectively, at OOUTC, May 10,1999; Poryoung for visble accumulated histogram method and Poryoung, Mokp'o and Kangnung for surface albedo method. In case of nighttime sea fog(18UTC, May 10, 1999), IR accumulated histogram method and Maximum brightness temperature method are used, respectively. Maxium brightness temperature method dectected sea fog better than IR accumulated histogram method with the charateristic value that is T_max < T_max_trs, and then T_max is beneath 700hPa temperature of GDAPS(Global Data Assimilation and Prediction System). Sea fog region which is detected by Maxium brighness temperature method was similar to the result of National Oceanic and Atmosheric Administratio/Advanced Very High Resolution Radiometer (NOAA/AVHRR) DCD(Dual Channel Difference), but usually visibility and relative humidity are not agreed well in inland.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.1
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• pp.1-9
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• 2020

ABL (Airborne Bathymetric LiDAR) is an advanced survey technology that uses green lasers to simultaneously measure the water depths and oceanic topography in coastal and river areas. Seabed point cloud extraction is an essential prerequisite to further utilizing the ABL data for various geographic data processing and applications. Conventional seabed detection approaches often use return waveforms. However, their limited accessibility often limits the broad use of the bathymetric LiDAR (Light Detection And Ranging) data. Further, it is often questioned if the waveform-based seabed extraction is reliable enough to extract seabed. Therefore, there is a high demand to extract seabed from the point cloud using other sources of information, such as geometric information. This study aimed to assess the feasibility of a ground filtering method to seabed extraction from geo-referenced point cloud data by using CSF (Cloth Simulation Filtering) method. We conducted a preliminary experiment with the RIGEL VQ 880 bathymetric data, and the results show that the CSF algorithm can be effectively applied to the seabed point segmentation.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.587-596
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• 2022

Sea levels are rising as a result of climate change, and low-lying areas along the coast are at risk of flooding. Therefore, we tried to investigate the relationship between sea level change and climate indices using satellite altimeter data (Topex/Poseidon, Jason-1/2/3) and southern oscillation index (SOI) and the Pacific decadal oscillation (PDO) data. If time domain data were converted to frequency domain, the original data can be analyzed in terms of the periodic components. Fourier transform and Wavelet transform are representative periodic analysis methods. Fourier transform can provide only the periodic signals, whereas wavelet transform can obtain both the periodic signals and their corresponding time location. The cross-wavelet transformation and the wavelet coherence are ideal for analyzing the common periods, correlation and phase difference for two time domain datasets. Our cross-wavelet transform analysis shows that two climate indices (SOI, PDO) and sea level height was a significant in 1-year period. PDO and sea level height were anti-phase. Also, our wavelet coherence analysis reveals when sea level height and climate indices were correlated in short (less than one year) and long periods, which did not appear in the cross wavelet transform. The two wavelet analyses provide the frequency domains of two different time domain datasets but also characterize the periodic components and relative phase difference. Therefore, our research results demonstrates that the wavelet analyses are useful to analyze the periodic component of climatic data and monitor the various oceanic phenomena that are difficult to find in time series analysis.

• Journal of Navigation and Port Research
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• v.48 no.3
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• pp.164-170
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• 2024

The light buoy, a floating structure at sea, is prone to drifting due to external factors such as oceanic weather. This makes it imperative to monitor for any loss or displacement of buoys. In order to address this issue, the Ministry of Oceans and Fisheries aims to issue alerts for buoy displacement by analyzing historical buoy position data to detect patterns. However, periodic lifting inspections, which are conducted every two years, disrupt the buoy's location pattern. As a result, new patterns need to be analyzed after each inspection for location monitoring. In this study, buoy position data from various periods were analyzed using convex hull and distance-based clustering algorithms. In addition, the optimal data collection period was identified in order to accurately recognize buoy location patterns. The findings suggest that a nine-week data collection period established stable location patterns, explaining approximately 89.8% of the variance in location data. These results can improve the management of light buoys based on location patterns and aid in the effective monitoring and early detection of buoy displacement.