• Proceedings of the Korea Water Resources Association Conference
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• 2003.05a
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• pp.151-158
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• 2003

Recently, there has been considerable interest in the influence of El Nino/Southern Oscillation (ENSO) on a global scale. ENSO has been measured by a simple index called Southern Oscillation Index (SOI). The statistical characteristics of SOI have been also focused to reveal the influence of ENSO. The SOI trend shows that El Nino events are generally getting stronger and more frequently occurring than La Nina events. However, the variation of SOI has varied significantly in a long-term. The SOI values are computed using the mean value and its standard deviation of the base period from 1951 to 1980. In the present study, the different base periods are applied to compute the SOI values and the influence of the different base periods is investigated in detail to reveal the long-term variation of SOI From the results, we could conclude that the present SOI should be carefully considered as a criterion to judge whether the El Nino and La Nina events are occurring.

• Water Engineering Research
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• v.2 no.2
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• pp.139-148
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• 2001

The teleconnections between El Nino/Southern Oscillation (ENSO) and droughts in Korea and the continental United States(U.S.) are investigated using cross analysis. For this purpose, monthly ENSO data and Palmer Drought Severity Index (PDSI) for Korea and for seven states in the U.S. are used. This study shows that there are significant statistical associations between ENSO indices and PDSI for Korea; however, the associations are very weak. It is found that dry conditions in Korea are positively correlated with El Nino, while wet conditions with La Nina. SOI, SSt in the Nino 4 and Ship track 6 regions among ENSO indices are more strongly correlated with PDSI than the other ENSO indices when using the original standardized data, but the SST Nino 3, SST Nino 4, and Darwin SSP exhibit abetter correlations with PDSI when using filtered data to be removed autocorrelation components of the original standardized data. The response time lag for maximum correlation between ENSO indices and PDSI appears to be affected by filtering the data. This is expecially true for Korea than for state analyzed in U.S. In addition, it is found that the PDSI in the continental U.S. is more strongly correlated wiht ENSO than in Korea. Furthermore, in analyzing the El Nino and La Nina aggregate composite data, it is found that the dry anomalies in Korea occur from the year following El Nino to about tow years after while the wet anomalies occur from La Nina year for a period of about two years.

• Journal of Climate Change Research
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• v.9 no.2
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• pp.171-179
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• 2018

The causal relationship between El Nino-Southern Oscillation (ENSO) and winter climate variability in Korea is tested by analyzing Korea Meteorological Administration Automatic Synoptic Observing System datasets for the past 59 years. Consistent with previous studies, positive phase of ENSO (El Nino) tends to cause warmer temperature and heavier precipitation in Korea in early winter with three-week lead time. This causality is quantified by performing Granger causality test. It turns out that ENSO explains an additional 9.25% of the variance of early-winter temperature anomalies in Korea, beyond that already provided by temperature itself. Likewise, 22.18% additional information is gained to explain early-winter precipitation variance by considering ENSO. This result, which differs from simple lead-lag correlation analysis, suggests that ENSO needs to be considered in predicting early-winter surface climate variability in Korea.

• Journal of Korea Water Resources Association
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• v.40 no.4
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• pp.299-311
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• 2007

Climatic abnormal phenomena involving El Nino and La Nina have been frequently reported in recent decades. The interannual climate variability represented by El Nino-Southern Oscillation (ENSO) is sometimes investigated to account for the climatic abnormal phenomena around the world. Although many hydroclimatologists have studied the impact of ENSO on regional precipitation and streamflow, however, there are still many difficulties in finding the dominant causal relationship between them. This relationship is very useful in making hydrological forecasting models for water resources management. In this study, the seasonal relationships between ENSO and hydrologic variables were investigated in Korea. As an ENSO indicator, Southern Oscillation Index (SOI) was used. Monthly precipitation, monthly mean temperature, and monthly dam inflow data were used after being transformed to the standardized normal index. Seasonal relationships between ENSO and hydrologic variables were investigated based on the exceedance probability and distribution of hydrologic variables conditioned on the ENSO episode. The results from the analysis of this study showed that the warm ENSO episode affects increases in precipitation and temperature, and the cold ENSO episode is related with decreases in precipitation and temperature in Korea. However, in some regions, the local relationships do not correspond with the general seasonal relationship.

• Journal of Korea Water Resources Association
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• v.38 no.12 s.161
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• pp.985-994
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• 2005

We examined problems of the principal component analysis(PCA), which is able to analyze at the low dimensionality as a methodologv to assess hydrologic time series, and introduced the theory and characteristics of independent component analysis(ICA) that can supplement problems of principal component analysis. We also applied the global sea surface temperature(SST) of the Nino region and assessed the correlation between El $\tilde{n}ino$-Southern Oscillation(ENSO) and SST. The results of examining separation-ability of principal components using mixed signals indicate that the independent component analysis is statistically superior compared to that of the principal component analysis. Finally, we assessed correlation between ENSO and global anomaly SST. The independent component analysis was applied to the $5^{\circ}{\times}5^{\circ}$(latitude and longitude) global anomaly SST in the Nino+3.4 region that is the El $\tilde{n}ino$ observation section. We assessed the correlation with the ENSO years. These results of the analysis show that only one independent component($86\%$) was able to represent the entire behavior and was consistent with the main ENSO years. Finally, we carried out independent component analysis for summer seasonal rainfalls at nine stations and could extract ICs to reflect geographical characteristics. The increasing trend has been shown at IC-1 and IC-2 since 1970s.

• Journal of the Korean earth science society
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• v.28 no.1
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• pp.35-44
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• 2007

This paper investigated the relationship between El $Ni\widetilde{n}o-Southern$ Oscillation (ENSO) and Indian Ocean Dipole (IOD) mode events and the impacts of these two phenomena on the climate, temperature and precipitation, of the Korean Peninsula. Data gathered from 1954 to 2004 were used for analysis, which included NINO 3 index, IOD index, and monthly mean precipitation and temperature at eleven locations in Korea. Statistical results showed that the IOD and ENSO were significantly correlated in Spring and Fall. It was clearly shown that the distribution of the sea surface temperature in the Indian Ocean has seen the Southern and Northern Oscillation in El $Ni\widetilde{n}o$ year, and Eastern and Western in IOD year. On the other hand, in El $Ni\widetilde{n}o$ you, the mean temperature of the Korea Peninsula was lower than normal in Summer and higher in Winter and its precipitation was more than normal in both Summer and Winter. However, significant correlation was not found in IOD year. In addition, the global atmospheric circulations during the major IOD years are less influential, unlike those of El $Ni\widetilde{n}o$ events.

• Proceedings of the Korea Water Resources Association Conference
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• 2002.05b
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• pp.1195-1204
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• 2002

The impacts of El Nino Southern Oscillation (ENSO) phenomenon on climate are widespread and extend far beyond the tropical Pacific. The phenomenon can be characterized by Southern Oscillation Index (SOI) which is derived from values of the monthly mean sea level pressure barometric difference between Tahiti and Darwin, Australia. Its best-known extreme is the El Nino event. In this study, general statistical characteristics of SOI and the data from which it is derived (i.e. mean sea level pressure data at Tahiti and Darwin) are presented as guidance when using SOI far other analyses. The characteristics include the availability of the barometric pressure data, statistics of monthly pressure data, correlation of SO intensity, frequency analysis of SOI by magnitude and by month (January-December), duration properties of SOI by run analysis.

• The Korean Journal of Quaternary Research
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• v.15 no.1
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• pp.53-61
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• 2001

To examine the effects of El Nino-Southern Oscillation (ENSO) on the tree growths of central Korea, tree rings of Korean pine(Pinus koraiensis) , Japanese red pine (Pinus densiflora) and yew (Taxus cuspidata) were analyzed. Korean pine and red pine samples were collected from 4 and 7sites in Sorak Mountain ranges, respectively ; yew from one site in Sobaek Mountain. Correlations between ring-width and monthly temperature data showed generally positive relationships for the Korean pine and yew chronologies, but negative ones for the red pine chronologies. In the analysis of correlation between ring-width and monthly S0 index data, only one Korean pine chronology at the lower Hangaerung valley site, and one red pine chronology at Baekdamjang shelter site showed significant relationships ; negative with April SOI for the former and positive with previous August-September SOI for the latter. The other chronologies at higher elevation sites did not indicate any significant correlations with SOI.

• Journal of the Korean earth science society
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• v.33 no.7
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• pp.583-595
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• 2012

The potential for tropical cyclogenesis in a given oceanic and atmospheric environments can be represented by genesis potential index (GPI). Using the 18 Coupled Model Inter Comparison Project phase 5 (CMIP5) models, the annual cycle of GPI and interannual variability of GPI are analyzed in this study. In comparison, the annual cycle of GPI calculated from reanalysis data is revisited. In particular, GPI differences between CMIP5 models and reanalysis data are compared, and the possible reasons for the GPI differences are discussed. ENSO (El Nino and Southern Oscillation) has a tropical phenomenon, which affects tropical cyclone genesis and its passages. Some dynamical interpretations of tropical cyclogenesis are suggested by using the fact that GPI is a function of four large-scale parameters. The GPI anomalies in El Nino or La Nina years are discussed and the most contributable factors are identified in this study. In addition, possible dynamics of tropical cyclogenesis in the Northern Hemisphere Pacific region are discussed using the large-scale factors.

• Journal of Environmental Science International
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• v.8 no.6
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• pp.645-652
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• 1999

In order to simulate and investigate the major characteristics of El Nino/Southern Oscillation(ENSO) and Madden Jullian Oscillation(MJO), an intermediate type atmosphere-ocean coupled model is developed and their results are examined. The atmosphere model is a time-dependent non-linear perturbation moist model which can determine the internal heating for itself. The counterpart of the atmosphere model is GCM-type tropical ocean model which has fine horizontal and vertical grid resolutions. In the coupled experiment, warm SST anomaly and increased precipitation and eastward wind and current anomalies associated with ENSO and MJO are properly simulated in Pacific and Indian Oceans. In spite of some discrepancies in simulation MJO, the observed atmospheric and oceanic low-frequency characteristics in the tropics are successfully identified. Among them, positive SST anomalies centered at the 100m-depth of tropical eastern-central Pacific due to the eastward advection of warm water and reduced equatorial upwelling, and negative anomalies in the Indian and western Pacific seem to be the fundamental features of tropical low-frequency oscillations.