Journal of the Korean Data and Information Science Society

The Korean Data and Information Science Society (한국데이터정보과학회)
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Density estimation of summer extreme temperature over South Korea using mixtures of conditional autoregressive species sampling model

혼합 조건부 종추출모형을 이용한 여름철 한국지역 극한기온의 위치별 밀도함수 추정

  • Jo, Seongil (Department of Statistics and Applied Probability, National University of Singapore) ;
  • Lee, Jaeyong (Department of Statistics, Seoul National University)
  • 조성일 (싱가포르 국립대학교 통계 및 응용확률학과) ;
  • 이재용 (서울대학교 통계학과)
  • Received : 2016.07.20
  • Accepted : 2016.09.02
  • Published : 2016.09.30
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Abstract

This paper considers a probability density estimation problem of climate values. In particular, we focus on estimating probability densities of summer extreme temperature over South Korea. It is known that the probability density of climate values at one location is similar to those at near by locations and one doesn't follow well known parametric distributions. To accommodate these properties, we use a mixture of conditional autoregressive species sampling model, which is a nonparametric Bayesian model with a spatial dependency. We apply the model to a dataset consisting of summer maximum temperature and minimum temperature over South Korea. The dataset is obtained from University of East Anglia.

기상 자료의 경우 한 지역의 기후가 인접지역의 기후와 비슷한 양상을 띄고 각 지역의 확률 밀도 함수 (probability density function)가 잘 알려진 확률 모형을 따르지 않는다는 것이 알려져 있다. 본 논문에서는 이러한 특성을 고려하여 이상 기후 현상이 뚜렷히 나타나는 여름철 평균 극한 기온(extreme temperature)의 확률 밀도 함수를 추정하고자 한다. 이를 위하여 공간적 상관관계 (spatial correlation)를 고려하는 비모수 베이지안 (nonparametric Bayesian) 모형인 조건부 자기회귀 종추출 혼합모형 (mixtures of conditional autoregression species sampling model)을 이용하였다. 자료는 이스트앵글리아 대학교 (University of East Anglia)에서 제공하는 전 지구의 최대 기온과 최소 기온자료 중 우리나라에 해당하는 지역의 자료를 사용하였다.

Keywords

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