Journal of Korea Water Resources Association (한국수자원학회논문집)

Korea Water Resources Association (한국수자원학회)
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Bias Correction for GCM Long-term Prediction using Nonstationary Quantile Mapping

비정상성 분위사상법을 이용한 GCM 장기예측 편차보정

  • Moon, Soojin (Dept. of Civil and Environmental Engineering, Dankook University) ;
  • Kim, Jungjoong (Dept. of Hydro-power, Isan Corporation) ;
  • Kang, Boosik (Dept. of Civil and Environmental Engineering, Dankook University)
  • 문수진 (단국대학교 공과대학 토목환경공학과) ;
  • 김정중 ((주) 이산 수공부) ;
  • 강부식 (단국대학교 공과대학 토목환경공학과)
  • Received : 2013.03.08
  • Accepted : 2013.05.14
  • Published : 2013.08.31
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Abstract

The quantile mapping is utilized to reproduce reliable GCM(Global Climate Model) data by correct systematic biases included in the original data set. This scheme, in general, projects the Cumulative Distribution Function (CDF) of the underlying data set into the target CDF assuming that parameters of target distribution function is stationary. Therefore, the application of stationary quantile mapping for nonstationary long-term time series data of future precipitation scenario computed by GCM can show biased projection. In this research the Nonstationary Quantile Mapping (NSQM) scheme was suggested for bias correction of nonstationary long-term time series data. The proposed scheme uses the statistical parameters with nonstationary long-term trends. The Gamma distribution was assumed for the object and target probability distribution. As the climate change scenario, the 20C3M(baseline scenario) and SRES A2 scenario (projection scenario) of CGCM3.1/T63 model from CCCma (Canadian Centre for Climate modeling and analysis) were utilized. The precipitation data were collected from 10 rain gauge stations in the Han-river basin. In order to consider seasonal characteristics, the study was performed separately for the flood (June~October) and nonflood (November~May) seasons. The periods for baseline and projection scenario were set as 1973~2000 and 2011~2100, respectively. This study evaluated the performance of NSQM by experimenting various ways of setting parameters of target distribution. The projection scenarios were shown for 3 different periods of FF scenario (Foreseeable Future Scenario, 2011~2040 yr), MF scenario (Mid-term Future Scenario, 2041~2070 yr), LF scenario (Long-term Future Scenario, 2071~2100 yr). The trend test for the annual precipitation projection using NSQM shows 330.1 mm (25.2%), 564.5 mm (43.1%), and 634.3 mm (48.5%) increase for FF, MF, and LF scenarios, respectively. The application of stationary scheme shows overestimated projection for FF scenario and underestimated projection for LF scenario. This problem could be improved by applying nonstationary quantile mapping.

분위사상법(QM, Quantile Mapping)은GCM(Global Climate Model) 자료의 계통적 오차를 보정하여 보다 신뢰성 높은 자료로 재생성하기 위해 활용되고 있다. 이 기법은 사상(mapping)시키려는 대상(object) 자료의 통계분포모수가 정상적(stationarity)이라는 가정 하에 대상 자료의 누적확률분포(CDF, Cumulative Distribution Function)를 목표(target) CDF에 통계적으로 투영시키는 것이 일반적이다. 따라서 GCM에서 제공되는 미래 기후시나리오의 강우시계열과 같이 비정상성(non-stationarity)을 갖는 장기 시계열자료에 대한 적용에는 문제점을 보이고 있다. 본 연구에서는 비정상성을 갖는 장기시계열자료의 오차보정을 위해 통계분포모수에 경향성을 부여하는 비정상성 분위사상법(NSQM, Nonstationary Quantile Mapping)을 적용하였다. NSQM 적용을 위한 확률분포로 수문분야에서 광범위하게 쓰이고 있는Gamma 분포를 선정하였으며, 대상 시나리오는 CCCma (Canadian Centre for Climate modeling and analysis)에서 제공하고 있는 CGCM3.1/T63모형의 20C3M(reference scenario)과 SRES A2 시나리오(projection scenario)를 활용하였다. 한강유역 내 관측기간이 충분한 10개의 지상관측소로부터 강우량을 수집하였다. 또한 6월과 10월사이에 연 강수량의 65% 이상이 집중되는 한반도의 계절성을 반영하기 위해 홍수기(6~10월)와 비홍수기(11~5월)를 구분하였고, 기준기간(Baseline)은 1973~2000년, 전망기간(Projection)은 2011~2100년으로 구분하였다. 다양한 목표분포의 설정을 통하여 NSQM의 적용성을 평가하고자 하였으며, 전망기간은 FF시나리오(Foreseeable Future Scenario, 2011~2040년), MF시나리오(Mid-term Future Scenario, 2041~2070년), LF시나리오(Long-term Future Scenario, 2071~2100년)의 3개의 구간으로 설정하여 기준기간과 전망기간의 연평균 강우량에 대한 경향성분석을 실시하였다. 그 결과NSQM이 FF시나리오에서 330.1mm(25.2%), MF시나리오에서 564.5mm(43.1%), LF시나리오에서 634.3mm(48.5%)로 증가하는 전망결과를 나타내고 있었다. 정상성기법을 적용한 결과, 전망기간 중 전체적으로는 동일한 평균값을 갖는 목표통계모수를 사용한다고 하여도, 전망전반부에서 과다하고, 후반부에서 오히려 과소한 전망을 보여주고 있었다. 이러한 결과는 비정상성기법을 사용함으로써 상당부분 개선될 수 있음을 확인하였다.

Keywords

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