• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.108-111
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• 2005

The Communication Ocean, Meteorological Satellite (COMS) as the one of the national space program has been developed by Korea Aerospace Research Institute (KARl). The Geostationary Ocean Color Imager (GOCI) is one of the main payloads ofCOMS which will provide consistent monitoring of ocean-colour around the Korean Peninsula from geostationary platforms. The ocean color observation from geostationary platform is required to remedy the coverage constraints imposed by polar orbiting platforms. In this paper the main characteristics of GOCI are described and compared with the current ocean color sensors. The GOCI will provide the measurement data of 6 visible channels and 2 nearinfrared channels (40Onm - 900nm). The high radiometric sensitivity is essential of ocean color sensor because of the weak water leaving radiance.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.04a
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• pp.45-54
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• 2003

This paper deal with the GPS performance for determining the ocean tidal loading components(M$_2$, N$_2$, S$_2$, K$_2$) and the availability of permanent GPS stations(CHJU, KANR) established in Korea. We determined the ocean tidal loading components from GPS observation by spectrum analysis and compared to that from global ocean tidal models(GOT00.2, FES99, CRS4.0, NAO99). Through this study, we have a sense that amplitude and phase lags of ocean tidal loading components from observed GPS data was almost equal to value calculated in ocean tide models. The diurnal ocean tide loading constituents are not considered, because unmodeled troposhere effects increase the noise level near the diurnal frequency band and prevent us from obtaining significant results.

• Journal of Astronomy and Space Sciences
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• v.23 no.4
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• pp.415-424
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• 2006

In this paper, requirements of Meteorological Administration about Meteorological Image. (MI) of Communications, Ocean and Meteorological Satellite (COMS) is analyzed for the design of COMS ground station and according to the analysis results, the distribution image size of each observation area suitable for satellite Field Of View (FOV) stated at the requirements of meteorological administration is determined and the precise satellite FOV and the size of distribution image is calculated on the basis of the image size of the determined observation area. The results in this paper were applied to the detailed design for COMS ground station and also are expected to be used for the future observation scheduling and the scheduling of distribution of user data.

• Proceedings of the Korean Aquaculture Society Conference
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• 2002.08a
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• pp.188-189
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• 2002

• Proceedings of KOSOMES biannual meeting
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• 2017.04a
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• pp.65-65
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• 2017

• Journal of Navigation and Port Research
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• v.31 no.6
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• pp.471-478
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• 2007

This study is carried out the investigation of nonlinear characteristics of the field wave observation data acquired in the western sea area in Jeju island during one year. It is aimed to offer the fundamental data for Freak wave forecasting in real sea. For this, the nonlinear parameters of ocean waves, which are Skewness, Atiltness, Kurtosis and Spectrum band width parameter et al., are introduced, and the parameters are compared and discussed with some characteristics wave components, ie, significant wave height, maximum wave height, and so on. As a results, we know that the parameters describe nonlinear characteristics of observed wave spectrum broadly, are feebly related with occurrence of abnormal maximum wave height, namely freak event, however the Kurtosis, $K_t$ which is a degree of peakness of mode of surface elevation distribution, has better relationship than others.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.30 no.6
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• pp.326-336
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• 2018

Continuous measurement of nearshore waves around Korea over long period is very demanding to setup plans for prevention of disasters of port and coastal structures. In this respect, a new web-based system, termed as WINK, was established, which collects nearshore wave data from Korea Meteorological Agency (KMA), Korea Hydrographic and Oceanographic Agency (KHOA), and Ministry of Oceans and Fisheries (MOF) and provide them after quality control of the data. This paper describes technical aspects regarding collection and selection of the wave observation data, construction of wave hindcasting data, the methodology of quality control for the selected wave data, and overall process of building the web-based data providing system.

• 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.

• Ocean and Polar Research
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• v.42 no.3
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• pp.195-210
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• 2020

The observed time series from the Korea Ocean Research Stations (KORS) in the Yellow and East China Seas (YECS) have various sources of noise, including bio-fouling on the underwater sensors, intermittent depletion of power, cable leakage, and interference between the sensors' signals. Besides these technical issues, intricate waves associated with background tidal currents tend to result in substantial oscillations in oceanic time series. Such technical and environmental issues require a regionally optimized automatic quality control (QC) procedure. Before the achievement of this ultimate goal, we examined the approach of the Ocean Observatories Initiative (OOI)'s standard QC to investigate whether this procedure is pertinent to the KORS. The OOI QC consists of three categorized tests of global/local range of data, temporal variation including spike and gradient, and sensor-related issues associated with its stuck and drift. These OOI QC algorithms have been applied to the water temperature time series from the Ieodo station, one of the KORS. Obvious outliers are flagged successfully by the global/local range checks and the spike check. Both stuck and drift checks barely detected sensor-related errors, owing to frequent sensor cleaning and maintenance. The gradient check, however, fails to flag the remained outliers that tend to stick together closely, as well as often tend to mark probably good data as wrong data, especially data characterized by considerable fluctuations near the thermocline. These results suggest that the gradient check might not be relevant to observations involving considerable natural fluctuations as well as technical issues. Our study highlights the necessity of a new algorithm such as a standard deviation-based outlier check using multiple moving windows to replace the gradient check and an additional algorithm of an inter-consistency check with a related variable to build a standard QC procedure for the KORS.

• Korean Journal of Remote Sensing
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• v.31 no.6
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• pp.513-521
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• 2015

In the processing of ocean color remote sensing data, spatio-temporal binning is crucial for securing effective observation area. The validity determination for given source data refers to the information in Level-2 flag. For minimizing the stray light contamination, NASA OBPG's standard algorithm suggests the use of large filtering window but it results in the loss of effective observation area. This study is aimed for quality improvement of ocean color remote sensing data by recovering/extending the portion of effective observation area. We analyzed the difference between MODIS/Aqua standard and modified product in terms of chlorophyll-a concentration, spatial and temporal coverage. The recovery fractions in Level-2 swath product, Level-3 daily composite product, 8-day composite product, and monthly composite product were $13.2({\pm}5.2)%$, $30.8({\pm}16.3)%$, $15.8({\pm}9.2)%$, and $6.0({\pm}5.6)%$, respectively. The mean difference between chlorophyll-a concentrations of two products was only 0.012%, which is smaller than the nominal precision of the geophysical parameter estimation. Increase in areal coverage also results in the increase in temporal density of multi-temporal dataset, and this processing gain was most effective in 8-day composite data. The proposed method can contribute for the quality enhancement of ocean color remote sensing data by improving not only the data productivity but also statistical stability from increased number of samples.