• Ocean and Polar Research
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• 제24권1호
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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.

• 한국수자원학회논문집
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• 제42권5호
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• pp.385-396
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• 2009

본 연구에서는 도시화나 지리지형적 특성에 따른 강수량의 분포와 추세를 분석하였다. 이를 위하여 서울을 포함하여 전국 56개 기후관측지점에서 1973년부터 2006년까지의 강수량 자료를 수집하여 분석을 실시하였다. 분석을 위하여 계절적 영향을 고려하여 1월, 4월, 7월 그리고 10월의 월평균 일별과 연평균 일별 강수량 추세를 분석하였다. 그리고 이들 연구지역에 대해서 GIS 분석을 이용하여 지리지형적 특성을 파악하였고, 도시화 정도를 파악하기 위하여 토지피복자료를 분석하였다. 연구결과 연평균 일별 강수량 추세는 대부분의 연구지역에서 증가하고 있으며, 4월과 10월의 강수량은 감소추세에 있고, 1월과 7월의 경우 증가추세에 있는 것으로 나타났다. 도시화 영향을 고려할 때, 강수량 변화는 연별이나 7월의 경우 증가추세를 보이나 1, 4, 10월 강수량의 경우 감소추세를 보였다. 또한 도시화율이나 해안 근접성과 비교하여 연구지역의 평균고도는 연평균 및 월평균 강수량 추세에 가장 중요한 영향을 미치고 있음을 알 수 있었다.

• 한국농공학회논문집
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• 제53권3호
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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.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2009년도 학술발표회 초록집
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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.

• 산업기술연구
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• 제21권B호
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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.

• 대한토목학회논문집
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• 제28권2B호
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• pp.237-248
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• 2008

우리나라에서 발생하는 강수량의 특성은 지협적인 원인이기 보다는 해수면 온도와 같은 기상 현상에 많은 영향을 받고 있다. 따라서 본 연구에서는 우리나라의 기상청에서 관측하는 61개 강우관측소의 월강수량과 범지구적 해수면 온도와의 상관관계를 분석하였다. 우리나라 강우량과 범지구적 해수면 온도와의 상관성 분석을 위해 군집분석과 주성분 분석을 통해 월강우량의 주요 성분을 추출하였다. 추출된 월강우량의 주요 성분과 범지구적 해수면 온도와의 상관성 분석을 통해 우리나라의 월강수량은 태평양에서 관측되는 해수면 온도와 통계적으로 유의한 상관관계를 갖는 해수면 온도 구역을 확인할 수 있었다. 또한, 월강수량의 Wavelet Transform 분석을 통해 2년과 4년 사이의 주기에서 강한 주성분을 갖는 것으로 나타났으며, 월강수량의 저빈도 특성을 확인할 수 있었다. 월강수량의 저빈도 주기 성분과 해수면 온도와의 상관성 분석에서 큰 상관성을 갖는 것으로 나타났으며, 이를 통해 해수면 온도를 이용한 강우량의 예측 가능성을 제시하였다.

• 한국수자원학회논문집
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• 제38권2호
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• pp.111-119
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• 2005

이 연구에서는 49년간 (1954-2002년) 한반도 기상 관측소 자료로부터 한강과 낙동강 유역의 유역평균 월강수량 시계열의 변동에 대한 기후특성을 분석하였다. 비록 두 유역의 연강수량의 크기는 차이가 있으나 월별 변동 특성은 매우 유사하였다. 특히 4월 유역평균 강수량은 감소 경향이 뚜렷하였고, 8월 유역평균 강수량은 증가 경향이 매우 뚜렷하였다. 또한 1970년 중반에 유역평균 월강수량의 변동에 변화가 나타났다. NINO3 지수와 한강과 낙동강 유역평균 월강수량 편차와의 동시상관분석으로부터 유역평균 9월 강수량은 NINO3 지수와 지속적인 음의 상관을 보였고, 11월 유역평균 강수량과는 양의 상관이 크게 나타났다.

• 한국방재학회 논문집
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• 제9권6호
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• pp.17-30
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• 2009

본 연구에서는 강수량, 월 최대강수량, 강수일수, 일강수량 20 mm, 30 mm 및 80 mm 이상인 일수의 장기추세의 통계적 유의성을 비모수 검정법인 Mann-Kendall 검정기법과 62개 지점의 1905년부터 2004년 기간 사이의 자료를 이용하여 분석하였다. 한반도 강수특성은 연강수량과 월 최대강수량의 증가, 강수일수 감소 그리고 20 mm, 30 mm, 80 mm 이상의 일강수를 가진 강수일수 증가로 요약될 수 있다. 또한 자료의 월별 추세분석 결과는 1, 5, 6, 7, 8, 9월 강수량과 월 최대강수량은 증가추세를 보이고 3, 4, 10, 11, 12월에는 감소추세를 보인다. 또한 6, 7, 8, 9월의 일강수량 20 mm와 30 mm 이상인 강수일수는 증가추세를 보였다. 그러나 Mann-Kendall 검정결과 90%와 95% 유의수준에 대하여 유의한 증감추세를 가지는 지점의 비율은 매우 낮았다. 이러한 결과는 각 변수의 선형 증감에 따른 장기 변동보다 자료들이 가지고 있는 분산형태의 불확실성이 매우 우세함을 의미하므로 수자원 계획 등에 반영하여야 할 것이다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2009년도 학술발표회 초록집
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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.

• 한국환경과학회지
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• 제2권3호
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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.