• Journal of the Korean earth science society
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• v.26 no.3
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• pp.268-275
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• 2005

One of the nonlinear statistical modelling, neural network method was applied to predict the Sea Surface Temperature Anomalies (SSTA) in the Nino regions, which represent El Nino indices. The data used as inputs in the training step of neural network model were the first seven empirical orthogonal functions in the tropical Pacific $(120^{\circ}\;E,\;20^{\circ}\;S-20^{\circ}\;N)$ obtained from the NCEP/NCAR reanalysis data. The period of 1951 to 1993 was adopted for the training of neural network model, and the period 1994 to 2003 for the forecasting validation. Forecasting results suggested that neural network models were resonable for SSTA forecasting until 9-month lead time. They also predicted greatly the development and decay of strong E1 Nino occurred in 1997-1998 years. Especially, Nino3 region appeared to be the best forecast region, while the forecast skills rapidly decreased since 9-month lead time. However, in the Nino1+2 region where they are relatively low by the influence of local effects, they did not decrease even after 9-month lead time.

• Journal of the Korean association of regional geographers
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• v.5 no.2
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• pp.143-153
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• 1999

This study is analyzed the correlation between El-Nino and La-Nina and Korea's temperature and precipitation in summer and winter, and the results of this analysis are as follows: (1) The extraction of the occurrences of El-Nino reveals are 5, but La-Nina reveals 6 years. (2) The tendency of change of sea surface temperature around NINO.3 and that of or country are about the same, but the anomaly of Janggi and Pusan was much greater than that of Inchon. (3) The anomaly of sea surface temperature around NINO.3 and that of the temperature showed the similar changing tendency, the temperature of Korea has something to do with that of NINO.3sea surface temperature as the correlation of ground temperature with the temperature of sea surface showed 0.06. Anomaly warm winter has something to do with El-Nino because the temperature of our country was high when El-Nino phenomena appeared. But the precipitation over our country is not significant for La-Nina. (4) Temperature in El-Nino year is lower than normal in summer and higher than normal in winter. But precipitation is more in summer and winter of El-Nino year, but it is not significant of La-Nina year.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.5 no.2
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• pp.86-94
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• 2000

In order to extract the spatio-temporal characteristics of long-term variability of the net heat flux on the sea surface in the East Asian marginal seas, empirical orthogonal function (EOF) analysis was conducted using data set calculated every 12 hours interval during 1978-1995. Among the first three modes explaining 73% of the total variance, the first mode having high peak at 1 year period indicates high variability area around the Sandong Peninsula and central and northeastern part of the East Sea. In the second mode which has spatial distribution of dipole type at the north and south, the peaks appear at 3.6 year and 2.3 year cycles. Time coefficient of the second EOF is believed to have close relation with the E1 Nino and has out-of-phase variation with NINO3 SST. Lagged correlation between NINO3 SST and time coefficient of the second EOF indicates four month time delay in the NINO3 SST. In the third mode which has opposite sign at the east and west, the periodicity of 6-9 year cycle has relatively clear appearance compared to other two EOFs. Also, high heat loss exceeding 800 W/$m^{2}$ in winter time occured at the south part of the Sandong Peninsula and Vladivostok. It reveals more frequent occurrence of about two times at the Sandong Peninsula than Vladivostok. The event is concentrated in January at Vladivostok, but it occurs primarily in December and January at the Sandong Peninsula.

• Journal of the Korean earth science society
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• v.26 no.7
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• pp.706-713
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• 2005

Subsurface oceanic data (Z20; Depth of $20^{\circ}C$ isotherm and WWV; Warm Water Volume) from the tropical Pacific Ocean from 1980 to 2004 were utilized to examine upper ocean variations in relation to E1 Nino. Time series analysis using EOF, composite, and cross-correlation methods indicated that there are significant time delays between subsurface oceanic parameters and the Nino3.4 SST. It implied that Z20 and WWV would be more reliable predictors of El Nino events. Based on analyzed results, we also constructed neural network model to predict the Nino3.4 SST from 1996 to 2004. The forecasting skills for the model using WWV were statistically higher than that using the trade wind except for short range forecasting less than 3 months. This model greatly predicted SST than any other previous statistical model, especially at lead times of 5 to 8 months.

• Journal of the Korean association of regional geographers
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• v.4 no.2
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• pp.151-164
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• 1998

I analyzed the correlation between El-Nino phenomenon and our country's temperature and precipitation laying the stress on the anomaly, and the result of this analysis is as follows: (1) The extraction of the occurrences of El-Nino at the place of sea surface around Nino.3 which was known as the sea area under observation for El-Nino reveals that there are 9 years (1969, 1970, 1973, 1977, 1987, 1992, 1995, 1998) when the temperature anomaly in January is more than 1.0 during the period of research years ($1969{\sim}1998$). (2) The tendency of change of sea surface temperature around Nino.3 and that of our country are about the same, but the anomaly of Pusan and Inchon was much greater than that of Jangki in the East Coast. (3) The anomaly of sea surface temperature around Nino.3 and that of the ground temperature showed the similar changing tendency, the temperature of our country has something to do with that of sea surface as the correlation of ground temperature with the temperature of sea surface showed 0.31. Anomaly warm winter has something to do with El-Nino because the temperature of our country was high when El-Nino phenomenon appeared. (4) As for the precipitation, we can see that it has generally increased after 1989 when the phenomenon of warm climate was intense than before that year. But as we study the change of anomaly, the precipitation has less correlation in comparison with the ground temperature. The precipitation in 1973, 1983 and 1987 which were El-Nino years was correlated with El-Nino. While the change of sea surface temperature has showed a tendency of plus(+)increase since 1990, the precipitation has showed a tendency of minus (-)decrease. Therefore it seems that the temperature of sea surface has little correlation with the amount of rainfall.

• Journal of the Korean Society for Marine Environment & Energy
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• v.4 no.1
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• pp.24-37
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• 2001

Physical and chemical properties of the northest Equatorial Pacific between 5° and 12° N along 131.5 °W wore investigated in association with changes in water column structures during the summer seasons of 1998 and 1999. Climatic disturbances such as El Nino and La Nina, should have affected this area during the study Period. In 1998, a thermocline where temperature rapidly decrease with depth, was formed at 90～110 m water depth. Nutrient depicting areas, specially for nitrate+nitrite and phosphate, or oligotrophic regions were extended down to approximately 100 m depth, which coincided with the surface mixed layer depth. However, in 1999, a very fluctuating thermocline was observed with latitudes. As a result of changes in the water column structures, nutrient concentrations also showed fluctuation parallel to the changes in other physical parameters. In the photic zone, depth integrated nitrogen and phosphorus values were 34 gN/m², 7 gP/m² in 1998 and 130 gN/m², 18 gP/m² in 1999, respectively. The results indicated that nitrogen (96 gN/m²) and phosphorus (11 gP/m²) are supported by up-welling and down-welling phenomena with convergence and divergence in the study area.

• Journal of Industrial Technology
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• v.31 no.B
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• pp.107-112
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• 2011

Recently, climate change around the world due to global warming has became an important issue and damages by climate change have a bad effect on human life. Changes of Sea Surface Temperature(SST) is associated with natural disaster such as Typhoon and El Nino. So we predicted daily future SST using Statistical Downscaling Method and CGCM 3.1 A1B scenario. 9 points of around Korea peninsular were selected to predict future SST and built up a regression model using Multiple Linear Regression. CGCM 3.1 was simulated with regression model, and that comparing Probability Density Function, Box-Plot, and statistical data to evaluate suitability of regression models, it was validated that regression models were built up properly.

• 한국해양학회지
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• v.9 no.2
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• pp.31-38
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• 1974

Concentration of heavy metals in the sediments from the sea off Jinhae and Masan have been studied. Concentration of the elements varied among the stations as the following: 0.32-0.76% Fe, 0.01-0.06% Mn, 29-120ppm Zn, 1-16ppm Co, 2-38 ppm Ni, 2.5-12.4ppm Pb and 0.2-0.7ppm Cd. General tendency of the concentraion of elements except Mn showed considerably high values at stations in the inner bay. This tendency seemed to be caused by waste water from industrial activities in the adjacent land. It can be thought that the pollution status of the studied area is still limited in the inner part of the day.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.10a
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• pp.290-294
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• 2001

Satellite data, with Sea Surface Temperature(SST) by NOAA and Sea Level(SL) by Topex/poseidon, are used to estimate characteristics on the variations and correlations of SST and SL in the East Asian Seas from January 1993 through May 1998. In the oceanic climate, the variations of SL shown the high values in the main current of Kuroshio and the variations of SST shown not the remarkable seasonal variations because of the continuos compensation of warm current by Kuroshio. In the continental climate, SL shown high variations in the estuaries(the Yellow River, the Yangtze River) with the mixing the fresh water in the mouth of estuaries of the saline water in the coasts of continent and SST shown highly the seasonal variations due to the climatic effect of continents. In the steric variations in summer, the eastern sea of Japan, the East China Sea and the western sea of Korea shown the increment of sea level with 10~20cm. But the Bohai bay in China shown relatively the high values of 20~30cm due to the continental climate. Generally the trends of SST and SL increased during all periods. That is say, the slopes of SST and SL presented 0.29$^{\circ}C$/year and 0.84cm/year, respectively. The annual and semi-annual amplitudes shown a remarkable variations in the western sea of Korea and the eastern sea of Japan.

• Ocean and Polar Research
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• v.43 no.1
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• pp.15-30
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• 2021

In this study, using 16 ORA-IP (Ocean Reanalysis Intercomparison Project) data, we investigated spatial and temporal changes of net surface heat flux in the East Asian seas and presented a new ensemble net surface heat flux index. The ensemble net surface heat flux index is produced considering the data distribution and the standard deviation of each ORA-IP. From the correlation analysis with air temperature averaged over the Korean Peninsula, ensemble net heat flux around the Korea Strait shows the highest correlation (0.731) with a 3 month time lag. For the correlation study regarding precipitation over the Korean Peninsula, it also shows significant correlation especially in winter and spring seasons. Similar results are also found in comparison with climate indices (AO, PDO, and NINO3.4), but ensemble net surface heat flux data in winter season reveals the strongest correlation patterns especially with winter temperature and spring precipitation.