• Proceedings of the KSRS Conference
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• v.1
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• pp.344-347
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• 2006

China Coastal Water (CCW) usually appears in the seas surrounding Jeju Island annually (June?October) and is very pronounced in August. The power spectrum density (PSD), sea level anomalies (SLAs), and sea surface temperatures (SSTs) were found to peak annually and semiannually. The peaks at intervals of 80-, 60-, and 43-days are considered to be influenced by CCW and the Kuroshio Current. Generally, low-salinity water appears to the west of Jeju Island from June through October and gradually propagates to the east, where CCW meets the Tsushima Current. Empirical orthogonal function (EOF) analysis of SLAs and SSTs indicated that the variance in SLAs and SSTs was 55.70 and 98.09% in the first mode, respectively. The PSD for the first mode of EOF analysis of SLAs was stronger in the western than in the eastern waters because of the influence of CCW. The PSD for the EOF analysis of SSTs was similar in all areas (the Yangtze Estuary and the waters to the west and east of Jeju Island), with a period of approximately 260 days.

• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.397-402
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• 2006

China Coastal Water (CCW) usually appears in the seas surrounding Jeju Island annually (June-October) and is very pronounced in August. The power spectrum density (PSD), sea level anomalies (SLAs), and sea surface temperatures (SSTs) were found to peak annually and semiannually. The peaks at intervals of 80-, 60-, and 43-days are considered to be influenced by CCW and the Kuroshio Current. Generally, low-salinity water appears to the west of Jeju Island from June through October and gradually propagates to the east, where CCW meets the Tsushima Current. Empirical orthogonal function (EOF) analysis of SLAs and SSTs indicated that the variance in SLAs and SSTs was 55.70 and 98.09% in the first mode, respectively. The PSD for the first mode of EOF analysis of SLAs was stronger in the western than in the eastern waters because of the influence of CCW. The PSD for the EOF analysis of SSTs was similar in all areas (the Yangtze Estuary and the waters to the west and east of Jeju Island), with a period of approximately 260 days.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.27 no.4
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• pp.293-302
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• 1991

The anomalous sea level deviation or storm surge caused by the typhoon Thelma in 1987 are studied analysing tidal observation data at 7 stations in the south coast of Korean peninsula. The surges are calculated by subtracting the predicted tidal height from the observed tidal record. The tidal deviation at these stations along the coast are discussed in association with meteorological data. The sea level anomalies are studied by means of the empirical orthogonal function (EOF) analysis and the fast fourier transform (FFT) method. The results of analysis suggest that the peak value of surges are higher at the tidal stations in semi-enclosed bay and in long narrow channel than at the ones facing with the open sea. From the result of EOF analysis, the temporal and spatial fluctuations of storm surge can be described by the first EOF mode, which explains 63% of the total variances during the passage of typhoon Thelma. The deviation of storm surge in the studied areas indicates bi-modal peak during the passage of typhoon Thelma. From the results of FFT spectrum analysis, the peak of energy of autospectrum for surge, atmospheric pressure, and wind stress appeared at low frequency fluctuations band of 0.008-0.076 cph over the 4 stations. Auto-correlation function of surge showed periodicity, while that of atmospheric pressure and wind stress indicates no periodicity. The result of FFT analysis shows that the typhoon surges are related chiefly with the change of atmospheric pressure in an open bay (Cheju Harbor), but with the wind stress in a semi-enclosed bay (Yeosu Harbor).

• Korean Journal of Fisheries and Aquatic Sciences
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• v.30 no.2
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• pp.188-202
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• 1997

The seasonal variability of the sea surface winds over the last Sea of Korea (Japan Sea) is investigated by means of empirical orthogonal function (EOF) analysis. The combined representation of fields of three climatic variables by empirical orthogonal functions is discussed. The eigenvectors are derived from daily sea level pressure, wind speed and 10-day mean sea surface temperature (SST) during 15 years $(1978\~1992)$. The spatial patterns of the mean pressure are characterized by the high pressure in the western part and the low pressure in the eastern part. The spatial distribution of the standard deviation (SD) of pressure are characterized by max SD of 6.6 mb near the Vladivostok, and minima along the coast of the Japan. In Vladivostok, the maxima of SD of SST and south-north wind (WV) were also occurred. The representation of fields of individual meteorological variables by EOF shows that the first mode of the west-east wind (WU) explain over $47.3\%$ of the variance and the second mode of WU represents $30\%$. Especially, the first mode of the WV explain $70.9\%$ of the variance and their time series coefficients show 1-cpy, 0.5-cpy frequency spectrum. The spatial distribution of the first mode eigenvectors of SST are characterized by maximum near Vladivostok. The combined representation of fields of several variables (pressure, wind, SST) reveals that the first mode magnitudes of the variance of the combined eigenvectors (WU-PR) are increased. By means of this result, the 1-year peak and the 6-months peak are remarkable. In the three combined patterns (wind, pressure, SST), the second mode of the eigenvector (wind) is affected by the SST. Their time coefficients of the first mode show noticeable 1-year peak. The spectral analysis of the second mode shows broad seasonal signal with the period of 4-months and a significant peak of variability at 3-month period.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.10 no.1
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• pp.100-112
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• 2005

Soil temperature was measured from the surface to 40 cm depth at three stations with different heights in tidal flat of Gomso Bay, west coast of Korea, for one month in every season 2004 to examine the thermal structure and the variation. Mean temperature in surface layer was higher in summer and lower in winter than in lower layer, reflecting the seasonal variation of vertically propagating structure of temperature by heating and cooling from the tidal flat surface. Standard deviation of temperature decreased from the surface to lower layer. Periodic variations of solar radiation energy and tide mainly caused short term variation of soil temperature, which was also intermittently influenced by precipitation and wind. Time series analysis showed the power spectral energy peaks at the periods of 24, 12 and 8 hours, and the strongest peak appeared at 24 hour period. These peaks can be interpreted as temperature waves forced by variations of solar radiation, diurnal tide and interaction of both variations, respectively. EOF analysis showed that the first and the second modes resolved 96% of variation of vertical temperature structure. The first mode was interpreted as the heating antl cooling from tidal flat surface and the second mode as the effect of phase lag produced by temperature wave propagation in the soil. The phase of heat transfer by 24 hour period wave, analyzed by cross spectrum, showed that mean phase difference of the temperature wave increased almost linearly with the soil depth. The time lags by the phase difference from surface to 10, 20 and 40cm were 3.2,6.5 and 9.8 hours, respectively. Vertical thermal diffusivity of temperature wave of 24 hour period was estimated using one dimensional thermal diffusion model. Average diffusivity over the soil depths and seasons resulted in $0.70{\times}10^{-6}m^2/s$ at the middle station and $0.57{\times}10^{-6}m^2/s$ at the lowest station. The depth-averaged diffusivity was large in spring and small in summer and the seasonal mean diffusivity vertically increased from 2 cm to 10 cm and decreased from 10 cm to 40 cm. Thermal propagation speeds were estimated by $8.75{\times}10^{-4}cm/s,\;3.8{\times}10{-4}cm/s,\;and\;1.7{\times}10^{-4}cm/s$ from 2 cm to 10 cm, 20 cm and 40 cm, respectively, indicating the speed reduction with depth increasing from the surface.