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• W2086228814 abstract "본 연구에서는 기후변화에 따른 수자원 영향평가를 위한 지역기후모형과 단계적 스케일링기법을 연계한 혼합상세화기법을 개발하고 그에 따른 적용성을 평가하고자 하였다. 단계적 스케일링기법은 강수량 구간을 총 3구간(극치호우사상, 무강수일수, 기타)으로 나누어 각 구간에 따라 각기 다른 방법을 적용하여 보정하는 기법으로, 극치호우사상은 회귀식을 이용한 보정기법, 무강수일수는 분위사상법, 나머지 부분은 평균 및 분산보정 기법을 적용하였다. 이 기법의 비교 평가를 위해 최근 혼합 상세화기법으로 가장 많이 적용되고 있는 선형보정기법, 분위사상법, 일기상발생기법을 활용하여 기상청 관할 기상관측소 61개 지점을 대상으로 적용성 평가를 수행하였다. 평가 결과, RCM에서 생산된 원자료 및 3가지 기존 기법(선형보정기법, 분위사상법, 일기상발생기법)으로 보정된 기후시나리오에 비해 본 연구에서 제안한 단계적 스케일링기법이 실제 기후특성을 잘 모의하는 것으로 나타나 적용성이 우수한 것으로 판단된다. 이러한 연구결과를 통해 단계적 스케일링기법은 RCM 사용이 증대될 기후변화 연구에 있어 그 활용성이 높을 것으로 기대된다. The objective of this study is to evaluate the hybrid downscaling method combined Step-Wise Scaling (SWS) method with Regional Climate Model (RCM) simulation data for climate change impact study on hydrology area. The SWS method is divided by 3 categories (extreme event, dry event and the others). The extreme events, wet-dry days and the others are corrected by using regression method, quantile mapping method, mean & variance scaling method. The application and evaluation of SWS method with 3 existing and popular statistical techniques (linear scaling method, quantile mapping method and weather generator method) were performed at the 61 weather stations. At the results, the accuracy of corrected simulation data by using SWS are higher than existing 3 statistical techniques. It is expected that the usability of SWS method will grow up on climate change study when the use of RCM simulation data are increasing." @default.
• W2086228814 created "2016-06-24" @default.
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• W2086228814 date "2013-06-30" @default.
• W2086228814 modified "2023-10-18" @default.
• W2086228814 title "Evaluation of Hybrid Downscaling Method Combined Regional Climate Model with Step-Wise Scaling Method" @default.
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• W2086228814 doi "https://doi.org/10.3741/jkwra.2013.46.6.585" @default.
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