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During the latest several decades, there has been considerable interest in revealing the relationship between El Niño-southern oscillation (ENSO) and hydro-meteorological variables. The oscillation is characterized by a simple index, the southern oscillation index (SOI). However, thus far, there is little evidence for the influence of ENSO in Korea and Japan. The influence of ENSO has also been studied in South Korea, but the estimated results are still qualitative and show an indirect relationship between ENSO and hydro-meteorological variables. In this study we use simple approaches to reveal the quantitative and direct correlation between SOI and the monthly precipitation at five stations distributed over South Korea. The monthly precipitation data are transformed into nonexceedance probability time series because the data cannot be normally distributed by applying the usual transformations. The SOI is classified into five categories according to their values. Additionally, to detect the nonlinear relationship between categorized SOI and nonexceedance probability of the monthly precipitation, we use Kendall's τ, a nonparametric test. Significant correlations between the categorized SOI and the transformed precipitation are detected. Generally, the monthly precipitation is influenced by a La Niña event with a lag time of 4 months for southern coastal areas and a lag time of 5 months for middle to high regions in South Korea.