한국농림기상학회지, 제 12권 제2호(2010) (pISSN 1229-5671, eISSN 2288-1859)
Korean Journal of Agricultural and Forest Meteorology, Vol. 12, No. 2, (2010), pp. 83~94
DOI: 10.5532/KJAFM.2010.12.2.083
ⓒ Author(s) 2014. CC Attribution 3.0 License.


우리나라의 연 강수량, 계절 강수량 및 월 강수량의 확률분포형 결정

김동엽, 이상호, 홍영주, 이은재, 임상준
서울대학교 산림과학부

(2010년 03월 02일 접수; 2010년 06월 23일 수정; 2010년 06월 23일 수락)

The Determination of Probability Distributions of Annual,
Seasonal and Monthly Precipitation in Korea

Dongyeob Kim, Sang Ho Lee, Youngjoo Hong, Eunjai Lee, Sangjun Im
Dept. of Forest Sciences, Seoul National University, San 56-1, Sillim 9-dong,
Gwanak-gu, Seoul, 151-921, Korea

(Received March 02, 2010; Revised June 23, 2010; Accepted June 23, 2010)

ABSTRACT
The objective of this study was to determine the best probability distributions of annual, seasonal and monthly precipitation in Korea. Data observed at 32 stations in Korea were analyzed using the L-moment ratio diagram and the average weighted distance (AWD) to identify the best probability distributions of each precipitation. The probability distribution was best represented by 3-parameter Weibull distribution (W3) for the annual precipitation, 3-parameter lognormal distribution (LN3) for spring and autumn seasons, and generalized extreme value distribution (GEV) for summer and winter seasons. The best probability distribution models for monthly precipitation were LN3 for January, W3 for February and July, 2-parameter Weibull distribution (W2) for March, generalized Pareto distribution (GPA) for April, September, October and November, GEV for May and June, and log-Pearson type III (LP3) for August and December. However, from the goodness-of-fit test for the best probability distributions of the best fit, GPA for April, September, October and November, and LN3 for January showed considerably high reject rates due to computational errors in estimation of the probability distribution parameters and relatively higher AWD values. Meanwhile, analyses using data from 55 stations including additional 23 stations indicated insignificant differences to those using original data. Further studies using more long-term data are needed to identify more optimal probability distributions for each precipitation.

Keyword: Probability distribution, Precipitation, L-moment, Average weighted distance (AWD)

MAIN

적요

본 연구의 목적은 우리나라의 연 강수량, 계절 강수량 그리고 월 강수량의 최적 확률분포형을 선정하는 것이다. 이를 위해서 전국 32개의 강우 관측소에서 얻은 자료에 대하여 L-모멘트 비 다이어그램과 평균가중거리 값을 이용하여 각 강수량별 최적 확률분포를 산정하였으며, 최종적으로 선정된 최적 확률분포형을 관측 지점별로 적합도 검정을 실시하였다. 그 결과, 연강수량에서는 3변수 Weibull 분포(W3), 봄과 가을에는 3변수 대수정규분포(LN3), 여름과 겨울에는 일반화된 극치분포(GEV)가 관측값에 가장 잘 적합하는 것으로 나타났다. 또한, 월 강수량에서는 1월은 LN3, 2월과 7월은 W3, 3월은 2변수 Weibull 분포(W2), 4월, 9월, 10월, 11월은 일반화된 Pareto 분포(GPA), 5월과 6월은 GEV, 그리고 8월과 12월은 log-Pearson typeIII 분포(LP3)가 가장 잘 적합하였다. 하지만, 최적 확률분포형의 지점별 적합도 검정의 결과, 1월, 4월, 9월, 10월, 11월의 GPA와 LN3에 대한 기각율이 확률분포의 매개변수 추정에서의 오류와 상대적으로 높은 AWD 값으로 인하여 매우 높게 나타났다. 한편, 23개 관측소의 자료를 추가하여 분석해본 결과 기존의 32개의 관측소 자료를 이용한 것과 큰 차이를 나타내지 않았다. 종합적으로 보다 적합한 확률분포형을 선정하기 위해서는 더 장기간의 표본자료를 이용한 추가적인 연구가 필요할 것으로 판단된다.

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