• 대기
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• 제34권1호
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• pp.55-67
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• 2024

This paper aims to provide a detailed introduction to the concept of the Ratio of Predictable Component (RPC) and the Signal-to-Noise Paradox. Then, we derive insights from them by exploring the paradoxical features by conducting a seasonal and regional analysis through ensemble expansion in KMA's climate prediction system (GloSea). We also provide an explanation of the ensemble generation method, with a specific focus on stochastic physics. Through this study, we can provide the predictability limits of our forecasting system, and find way to enhance it. On a global scale, RPC reaches a value of 1 when the ensemble is expanded to a maximum of 56 members, underlining the significance of ensemble expansion in the climate prediction system. The feature indicating RPC paradoxically exceeding 1 becomes particularly evident in the winter North Atlantic and the summer North Pacific. In the Siberian Continent, predictability is notably low, persisting even as the ensemble size increases. This region, characterized by a low RPC, is considered challenging for making reliable predictions, highlighting the need for further improvement in the model and initialization processes related to land processes. In contrast, the tropical ocean demonstrates robust predictability while maintaining an RPC of 1. Through this study, we have brought to attention the limitations of potential predictability within the climate prediction system, emphasizing the necessity of leveraging predictable signals with high RPC values. We also underscore the importance of continuous efforts aimed at improving models and initializations to overcome these limitations.

• 대기
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• 제23권4호
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• pp.425-441
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• 2013

This study investigates the projections of water cycle, budget and river discharge over land in the world at the end of twenty-first century simulated by atmosphere-ocean climate model of Hadley Centre (HadGEM2-AO) and total runoff integrating pathways (TRIP) based on the RCP scenario. Firstly, to validate the HadGEM2-AO hydrology, the surface water states were evaluated for the present period using precipitation, evaporation, runoff and river discharge. Although this model underestimates the annual precipitation about 0.4 mm $mon^{-1}$, evaporation 3.7 mm $mon^{-1}$, total runoff 1.6 mm $mon^{-1}$ and river discharge 8.6% than observation and reanalysis data, it has good water balance in terms of inflow and outflow at surface. In other words, it indicates the -0.3 mm $mon^{-1}$ of water storage (P-E-R) compared with ERA40 showing -2.4 mm $mon^{-1}$ for the present hydrological climate. At the end of the twenty-first century, annual mean precipitation may decrease in heavy rainfall region, such as northern part of South America, central Africa and eastern of North America, but for increase over the Tropical Western Pacific and East Asian region. Also it can generally increase in high latitudes inland of the Northern Hemisphere. Spatial patterns of annual evaporation and runoff are similar to that of precipitation. And river discharge tends to increase over all continents except for South America including Amazon Basin, due to increased runoff. Overall, HadGEM2-AO prospects that water budget for the future will globally have negative signal (-8.0~-0.3% of change rate) in all RCP scenarios indicating drier phase than the present climate over land.

• 대한토목학회논문집
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• 제29권2B호
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• pp.193-205
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• 2009

태풍은 열대태평양 지역에서 발생하여 북상하면서 우리나라에 영향을 끼치게 되며, 태풍이 우리나라를 지나면서 강풍과 호우를 통하여 자연재해를 유발시키게 된다. 따라서 본 연구에서는 태풍으로 인해 발생하는 호우 사상을 여러 통계적 기법을 통해 정량적으로 평가하였다. 첫 번째로 빈도해석을 통해 확률강우량과 태풍 확률강우량을 산정하여 비교하였다. 두 번째로 미공병단에서 개발한 EST 기법을 통해 태풍의 극치강우량을 평가하여 EST 확률강우량을 산정하였다. 마지막으로 비매개변수적 모의발생기법과 지역가중다항식을 결합하여 태풍에 의한 NL 확률강우량을 추정하였다. 분석결과에서 대상지점 중에서 강릉과 목포는 태풍의 영향을 다른 지점에 비해 많이 받으며, 서울과 인천은 태풍에 의한 호우의 영향이 미비한 것으로 나타났다. 또한, EST 확률강우량과 NL 확률강우량은 관측 자료를 이용하여 장기간의 모의를 통하여 quantile을 산정하므로 주요 수공구조물과 태풍의 영향이 큰 지역에서는 이를 검토할 필요성이 있으며, 태풍특성인자의 모의를 통하여 강우량을 평가하므로 지구온난화 등에 따른 기후변화의 영향에 대한 연구에 활용 할 수 있다.