R/S 기법을 이용한 지역별 월 강수량 자료의 자기유사성 평가 = Evaluation of Self-similarity on Regional Monthly Precipitation using ReScaled Analysis Method

다국어 초록 (Multilingual Abstract)

It has been reported the steep increasement of natural hazards in recent, that was caused byflood or drought with the abrupt climate change. It was raised the concern about the predictionmethod for the climate change and then it has been tried to apply the fractal analysis method tomodel such random natural phenomenon for last a couple of decades. But it looks like that theappropriate research results was not reported enough yet. In this study, it was estimated the Hurstexponent(H), as one of tool to apply fractal theory to natural system, to evaluate the self-similarityof monthly precipitation data of 64 climate stations in Korea. It was shown a range ofH=0.97~0.99, and was H>1/2 that is the obvious evidence of self-similarity in the variations ofmonthly precipitation data. As a result, It was verified that abnormal precipitation trends show theself-similarity and Hurst exponent could be apply to the prediction of future behavior ofprecipitation variation in Korea.

국문 초록 (Abstract)

최근 강우 발생빈도의 불규칙한 변화로 홍수 및 가뭄 피해가 증가함에 따라 불규칙한 자연현상의 특성을 예측하는 확률론적 방안들이 관심을 받고 있다. 본 연구에서는 자연계 현상을 확률론적으로 예측하는 기법인 플랙탈이론의 허스트지수(Hurst exponent)를 이용한 자기유사성 평가를 전국 64개 기상관측소의 월강수량 자료를 대상으로 실시하였다. 1986년부터 2015년까지 총 30년 동안의 월강수량을 평가한 결과 허스트지수는 H=0.97~0.99의 범위로 나타났다. 이는 H>1/2의 양의 상관관계를 보이며, 자기유사성을 가지는 것으로 평가될 수 있어 기존의 축척된 자료를 통해 향후의 이상강우에 대한 예측이가능하다는 사실을 보여주는 것으로 나타났다.

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