• Ocean and Polar Research
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• v.24 no.1
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• pp.19-31
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• 2002

Precipitation variability around King Sejong Station related with E1 $Ni\~{n}o$/Southern Oscillation (ENSO) is evaluated using the gauge-based monthly data of its neighboring stations. Though three Ant-arctic Stations of King Sejong (Korea), Frei (Chile), and Artigas (Uruguay) are all closely located within 10 km, their precipitation data show mostly insignificant positive or rather negative correlations among them in the annual, seasonal and monthly precipitation. This result indicates that there are locally large variations in the distribution of precipitation around King Sejong Station. The monthly data of Frei Station for 31 years (1970-2000) are analyzed for examining the ENSO signal in precipitation because of its longer precipitation record compared to other two stations. From the analysis of seasonal precipitation, it is seen that there is a tendency of less precipitation than the average during E1 $Ni\~{n}o$ events. This dryness is more distinct in fall to spring seasons, in which the precipitation decreases down to about 30% of seasonal mean precipitation. However, the precipitation signal related with La $Ni\~{n}a$ events is not significant. From the analysis of monthly precipitation, it is found that there is a strong negative correlation during 1980s and in the late 1990s, and a weak positive correlation in the early 1990s between normalized monthly precipitation at Frei Station and Sea Surface Temperature (SST) anomalies in the $Ni\~{n}o$ 3.4 region. However, this relation may be not applied over the region around King Sejong Station, but at only one station, Frei.

• Journal of Korea Water Resources Association
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• v.42 no.5
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• pp.385-396
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• 2009

The spatial distribution of precipitation trends according to urbanization, geographical and topographical conditions have been studied. In this study, precipitation data from 1973 to 2006 were analyzed for 56 climatological stations including the Seoul metropolis in South Korea. In addition to annual average daily precipitation, monthly average daily precipitation in April, July, October and January were analyzed, considering seasonal effect. The geographical and topographical characteristics of these sites were examined using GIS analysis. Land use status of the study area was also examined to estimate the extent of urbanization. The study results indicate that annual average precipitation increased, and monthly average precipitation in April and October decreased, while those in January and July increased. Considering urbanization effect, annual average precipitation and monthly average precipitation in July increased; however, monthly average precipitation in January, April and October decreased. Furthermore, compared with urbanization rate and proximity to coast, average elevation of study area appeared to be the most close correlation with annual and monthly averages of precipitation trends.

• Journal of The Korean Society of Agricultural Engineers
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• v.53 no.3
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• pp.1-11
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• 2011

The temporal variability of spring (March, April, May) monthly precipitation, precipitation effectiveness, monthly maximum precipitation, monthly precipitation of different durations, and the precipitation days over several threshold (i.e. 0, 10, 20, 30, 40, and 50 mm/day) of 59 weather stations between 1973 and 2009 were analyzed. Also to analyze the regional characteristics of temporal variability, 59 weather stations were classified by elevations, latitudes, longitudes, river basins, inland or shore (east sea, south sea, west sea) area and the level of urbanization. Results demonstrated that trends of variables increase in April and decrease in May except precipitation day. Overall trend of precipitation amount and precipitation effectiveness is same but precipitation effectiveness of several sites decrease despite the trend of precipitation amount increases which may be caused by the air temperature increase. Therefore more effective water supply strategy is essential for Spring season. Regional characteristics of Spring precipitation variability can be summarized that increase trend during May become stronger with the increase of latitude and elevation which is similar to that of Summer season. The temporal variability of variables showed different behaviors according to river basins, inland or shore (east sea, south sea, west sea) area and the level of urbanization.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.1260-1264
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• 2009

Precipitation time series is a mixture of complicate fluctuation and changes. The monthly precipitation data of 61 stations during 36 years (1973-2008) in Korea are comprehensively analyzed using the EOFs technique and CSEOFs technique respectively. The main motivation for employing this technique in the present study is to investigate the physical processes associated with the evolution of the precipitation from observation data. The twenty-five leading EOF modes account for 98.05% of the total monthly variance, and the first two modes account for 83.68% of total variation. The first mode exhibits traditional spatial pattern with annual cycle of corresponding PC time series and second mode shows strong North South gradient. In CSEOF analysis, the twenty-five leading CSEOF modes account for 98.58% of the total monthly variance, and the first two modes account for 78.69% of total variation, these first two patterns' spatial distribution show monthly spatial variation. The corresponding mode's PC time series reveals the annual cycle on a monthly time scale and long-term fluctuation and first mode's PC time series shows increasing linear trend which represents that spatial and temporal variability of first mode pattern has strengthened. Compared with the EOFs analysis, the CSEOFs analysis preferably exhibits the spatial distribution and temporal evolution characteristics and variability of Korean historical precipitation.

• Journal of Industrial Technology
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• v.21 no.B
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• pp.241-248
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• 2001

Normally at a flood season the operation of the dam depends on a short range weather forecast that makes many difficulties of the management at a dry season. It is needed to study the pattern of the long period rainfall. The concept of PMP(Probable Maximum Precipitation) was used for designing dam. From the concept, this study is applied the concept of monthly probable maximum precipitation for operating dam. It can be possible to let us know the appropriateness of a limiting water level at a rainy season. For the operation of dam at a dry season this study can predict roughly the flood season's pattern of precipitation by month or period, therfore the prediction of precipitation can rise efficient operation of a dam.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.2B
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• pp.237-248
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• 2008

Precipitation variability in Korea is mainly influenced by climate circulation such as sea surface temperature, not a local convection. Therefore, this study investigates relationship between monthly precipitation of 61 station observed by Korea Meteorological Administration and global sea surface temperatures (SSTs). The main components of monthly precipitation in Korea are extracted by a method which consists of the principal analysis combined with the cluster analysis, to examine the correlation between monthly rainfalls and SSTs. The relationships between main components of monthly precipitation and SSTs exists in Pacific Ocean. At the result of Wavelet Transform analysis, The 2-4 year band have a strong wavelet power spectrum and the low frequency. the correlation coefficient between low frequency components of monthly rainfalls and SSTs calculated bigger then correlation coefficient between main components and SSTs. Hence, these results propose a prediction possibility of monthly precipitations using the varition of SSTs.

• Journal of Korea Water Resources Association
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• v.38 no.2
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• pp.111-119
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• 2005

The climatological characteristics of the area averaged monthly precipitation over the Han- and Nakdong-river basins were investigated. The data used for this study is monthly precipitation data from 51 meteorological stations for the period of 1954 to 2002. The magnitude of area averaged precipitation in the Han-river basin was about 10% larger than that in the Nakdong-river basin. However, the variability of two monthly precipitation time series exhibited similar characteristics: April precipitation tends to decrease and August precipitation increase significantly, while there was no significant trend for the other months. There were some indications of abrupt change around the 1970's in the periodicity of precipitation and relationship with El Nino index. September precipitation showed negative correlation with NINO3 index but November precipitation, positive correlation with NINO3 index, indicating a possible connection with the global-scale phenomena.

• Journal of the Korean Society of Hazard Mitigation
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• v.9 no.6
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• pp.17-30
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• 2009

In this study, the existence of possible deterministic longterm trend of precipitation amount, monthly maximum precipitation, rain day, the number of rain day greater than 20mm, 30mm, and 80mm was analyzed using the Mann-Kendall rank test and the data from 62 stations between 1905 and 2004 in South Korea. Results indicate that the annual and monthly rainfall amount increases and the number of rain days which have more than 80mm rainfall a day, increases. However the number of rain days decreases. Also, monthly trend analysis of precipitation amount and monthly maximum precipitation increases in Jan., May, Jun., Jul., Aug., and Sep. and they decrease in Mar., Apr., Oct., Nov., and Dec. Monthly trend of the number of rain day greater than 20mm, 30mm, and 80mm increases in Jun., Jul., Aug., and Sep. However results of Mann-Kedall test demonstrated that the ratio of stations, which have meaningful longterm trend in the significance level of 90% and 95%, is very low. It means that the random variability of the analyzed precipitation related data is much greater than their linear increment.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.112-115
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• 2009

The research of climate change impact in hydrometeorology often relies on climate change information. In this paper, neural networks models such as support vector machine neural networks model (SVM-NNM) and multilayer perceptron neural networks model (MLP-NNM) are proposed statistical downscaling of the monthly precipitation. The input nodes of neural networks models consist of the atmospheric meteorology and the atmospheric pressure data for 2 grid points including $127.5^{\circ}E/35^{\circ}N$ and $125^{\circ}E/35^{\circ}N$, which produced the best results from the previous study. The output node of neural networks models consist of the monthly precipitation data for Seoul station. For the performances of the neural networks models, they are composed of training and test performances, respectively. From this research, we evaluate the impact of SVM-NNM and MLP-NNM performances for the downscaling of the monthly precipitation data. We should, therefore, construct the credible monthly precipitation data for Seoul station using statistical downscaling method. The proposed methods can be applied to future climate prediction/projection using the various climate change scenarios such as GCMs and RCMs.

• Journal of Environmental Science International
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• v.2 no.3
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• pp.179-191
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• 1993

This paper aims to know the characteristics of occurrence of the anomaly level and variability of the monthly precipitation in Kyeongnam, Korea. For this study, it was investigated 주e distribution of the annual and cont비y mean precipitation, the precipitation variability and its annual change, and the characteristics of occurrence of the anomaly level in Kyeongnam area the results were summarized as follows : 1) she mean of annual total precipitation averaged over Kyeongnam area is 1433.3mm. I'he spatial distribution of the annual total precipitation shows that in Kyeongnam area, the high rainfall area locates in the southwest area and south coast and the low rainfall area in an inland area. 2) Monthly mean precipitation in llyeongnam area was the highest in July(266.4mm) 각lowed by August(238.0mm), June(210.2mm) in descending order. In summer season, rainfall was concentrated and accounted for 49.9 percent of the annual total precipitation. Because convergence of the warm and humid southwest current which was influenced by Changma and typhoon took place well in this area. 3) The patterns of annual change of precipitaion variability can be divided into two types; One is a coast type and the other an inland type. The variability of precipitation generally appears low in spring and summer season and high in autumn and winter season. This is in accord with the large and small of precipitation. 4) The high frequency of anomaly level was N( Normal)-level and the next was LN( Low Informal) -level and 25(Extremely Subnormal)-level was not appeared in all stations. The occurrence frequency of N level was high in high rainfall area and distinguish성 in spring and summer season but the low rainfall area was not. hey Words : anomaly level, variability, precipitation, coast type, inland type.