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수문기상학적 활용을 위한 레이더 강우자료 생산(I) : 편의보정 및 오차분포 산정

Generation of radar rainfall data for hydrological and meteorological application (I) : bias correction and estimation of error distribution

  • 김태정 (전북대학교 토목공학과, 방재연구센터) ;
  • 이동률 (한국건설기술연구원 수자원.하천연구소) ;
  • 장상민 (APEC 기후센터, 응용사업본부, 응용사업팀) ;
  • 권현한 (전북대학교 토목공학과, 방재연구센터)
  • Kim, Tae-Jeong (Department of Civil Engineering, Chonbuk National University) ;
  • Lee, Dong-Ryul (Water Resources Research Division, Korea Institute of Civil Engineering and Building Technology) ;
  • Jang, Sang-Min (Climate Application Team, APEC Climate Center) ;
  • Kwon, Hyun-Han (Department of Civil Engineering, Chonbuk National University)
  • 투고 : 2016.11.01
  • 심사 : 2016.11.22
  • 발행 : 2017.01.31

초록

최근 기후변화로 인하여 발생하는 기상재해 및 위험기상 현상의 대비를 위하여 조밀한 시공간적 해상도를 갖는 레이더 강우가 활용되고 있지만 널리 사용되는 Marshall-Palmer의 Z-R 관계식으로 추정된 레이더 강우는 과소추정의 문제점이 있다. 본 연구는 이러한 문제점을 해결하기 위하여 분위회귀 분석기법을 통한 레이더 강우자료 편의보정 기법과 Copula 함수를 연계한 강우자료 확충기법을 개발하였다. 본 연구에서 개발된 모형을 통하여 편의가 보정된 시계열 레이더 강우자료 효율을 통계적으로 분석한 결과 우수한 모형성능을 확인하였으며 Copula 기법을 이용하여 지상강우 및 레이더 강우자료를 확충한 결과 기존의 강우특성을 현실적으로 재현하는 것을 확인하였다. Copula 기법을 통한 강우자료 확충기법은 레이더 강우의 오차분포를 평가하는데 유용하게 활용될 것으로 판단된다.

Information on radar rainfall with high spatio-temporal resolution over large areas has been used to mitigate climate-related disasters such as flash floods. On the other hand, a well-known problem associated with the radar rainfall using the Marshall-Palmer relationship is the underestimation. In this study, we develop a new bias correction scheme based on the quantile regression method. This study employed a bivariate copula function method for the joint simulation between radar and ground gauge rainfall data to better characterize the error distribution. The proposed quantile regression based bias corrected rainfall showed a good agreement with that of observed. Moreover, the results of our case studies suggest that the copula function approach was useful to functionalize the error distribution of radar rainfall in an effective way.

키워드

참고문헌

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