• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.3 no.1
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• pp.16-24
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• 1998

In this study, Ocean General Circulation Model (OGCM) has been developed as a counterpart of Atmospheric General Circulation (AGCM) for the study of coupled ocean-atmosphere climate system. The oceanic responses to given atmospheric boundary conditions have been investigated using the OGCM. In an integration carried out over 100 simulated years with climatological monthly mean data (EXP 1), most parts of the model reached a quasi-equilibrium climate reproducing many of the observed large-scale oceanic features remarkably well. Some observed narrow currents, however, such as North Equatorial Counter Current, were inevitably distorted due to the model's relatively coarse resolution. The seasonal changes in sea ice cover over the southern oceans around Antarctica were also simulated. In an experiment (EXP 2) under boundary condition of 10-year monthly data (1982-1991) from NCEP/NCAR Reanalysis Project model properly reproduced major oceanic changes during the period, including El Ni$\tilde{n}$os of 1982-1983 and 1986-87. During the ENSO periods, the experiment showed eastward expansion of warm surface waters and a negative vertical velocity anomalies along' the equator in response to expansion of westerly current velocity anomalies as westerly wind anomalies propagated eastward. Simulated anomalous distribution and the time behavior in response to El Ni$\tilde{n}$o events is consistent with that of the observations. These experiments showed that the model has an ability to reproduce major mean and anomalous oceanic features and can be effectively used for the study of ocean-atmosphere coupling system.

• Journal of Korea Water Resources Association
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• v.34 no.4
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• pp.347-356
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• 2001

Even though the increase of greenhouse gases such as $CO_2$ is thought to be the main cause for global warming, its impact on global climate has not been revealed clearly in rather quantitative manners. However, researches using Genral Circulation Model(GCM) has shown that the accumulation of greenhouse gases increases the global mean temperature, which in turn impacts on the global water circulation pattern. A climate predictive capability is limited by lack of understanding of the different process governing the climate and hydrologic systems. The prediction of the complex responses of the fully coupled climate and hydrologic systems can be achieved only through development of models that adequately describe the relevant process at a wide range of spatial and temporal scales. These models must ultimately couple the atmospheres, oceans, and lad and will involve many submodels that properly represent the individual processes at work within the coupled components of systems. So far, there are no climate and related hydrologic models except local rainfall-runoff models in Korea. The purpose of this research is to predict the change of temperature in Korean Peninsula using regional scale model(IRSHAM96 model) and GCM data obtained from the increasing scenarios of $CO_2$ Korean Peninsula increased by $2.5^{\circ}C$ and the duration of Winter in $lxCO_2$ condition would be shorter the $2xCo_2$ condition due to global warming.

• Journal of the Korean earth science society
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• v.27 no.6
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• pp.653-658
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• 2006

The seasonal predictability of typhoon activity over the western North Pacific is investigated using an atmospheric general circulation model GCPS. A ten-member ensemble with different initial conditions is integrated for five months using observed sea surface temperature data for each year from 1979 to 2003. It is shown that the monthly variation of occurrence frequency of simulated tropical storms and the distribution of tropical storm genesis location are similar to those of observed tropical storms, but the model is unable to reliably predict the interannual variation of the occurrence frequency of tropical storms. This is largely because the observed relationship between tropical storm occurrence frequency and ENSO is different from the simulated one. Unlike the observation, in which the tropical storm occurrence frequency has no relation to ENSO, the model has a tendency to generate more (less) tropical storms than normal during El Nino (La Nina). On the other hand, the interannual variation of the mean longitude of tropical storms that shows a close connection with ENSO in both observations and simulations is simulated similar to the observation.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.176-176
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• 2021

한반도의 강수를 예측하는 것은 수자원 관리 측면에서 매우 중요하다. 한반도의 강수는 연별 변동 뿐 아니라 계절별로 변동을 갖는다. 우리는 이 중 건기(Dry period)의 가뭄과 그 이후 농번기(3월, 4월)에 영향을 미치는 초겨울(11월, 12월)의 강수를 예측은 수자원 관리에 있어서 중요한 의미를 갖는다. 본 연구에서는 Regularized regression 모형인 Elastic net model을 이용하여 중장기 (7개월 이상)기반으로 초겨울의 강우 예측의 가능성에 대해서 논하고자 한다. 특히, 본 연구에서는 우리나라의 초겨울 강우의 변동이 대서양의 대규모의 대기 순환과 밀접한 관계를 보이는 것을 확인하였으며 이를 논하기 위해서 Sea Surface Temperature (SST) 등의 자료를 사용하여 분석하였다. 이 시간적 지체 효과를 갖고 있는 대기 순환은 Eurasia 지역을 기반으로 횡적인 순환과 관련이 깊은 것으로 파악되었다. 본 연구의 결과는 앞으로 우리나라의 가뭄관리에 유용하게 활용될 것으로 기대된다.

• Proceedings of the Korean Environmental Sciences Society Conference
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• 1997.10a
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• pp.10-12
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• 1997

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.16-16
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• 2017

기후 시스템의 다양한 상호작용으로 인해 나타나는 대표적 현상인 강우는 수문학적 분석 과정의 필수적인 요소이며 장기 강우를 예측하는 것은 효율적인 수자원 관리에 중요한 기반이 되고 있다. 이러한 강우는 장기적으로 지구의 대기-해양 순환 패턴의 영향을 받으며, 특히 엘니뇨와 라니냐와 같은 기상 이변이 발생할 경우 대규모 순환에 변화가 일어나게 되어 강우에 영향을 미칠 수 있다. 따라서 본 연구에서는 지구의 순환 패턴 특성을 수치화한 전지구적 기상인자 중에서 우리나라 장기 강우를 예측하기 위한 기상인자를 선정하고 시계열 모형 구축을 통하여 예측력을 평가하였다. 이를 위해 강우에 내재된 다양한 대기-해양 순환 패턴으로부터 나타나는 주기적 요소를 추출하기 위해 앙상블 경험적 모드분해법을 사용하여 강우를 분해한 후, 각 분해된 강우자료와 전지구적 기상인자와의 상관성 분석을 통해 높은 상관성을 가진 기상인자를 선별하고 단계식 변수선택법으로부터 유의미한 기상인자를 최종적으로 선정하였다. 그 결과, 우리나라 기상청 60개 지점의 월별 강우자료 중 전반적으로 영향을 미치는 기상인자를 선정할 수 있었으며, 선정된 기상인 자로 구축된 시계열 모형을 통해 우리나라 장기 강우를 예측하였다.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.120-124
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• 2008

본 연구에서는 대기대순환모형(GCM) 모의결과를 활용하여 한반도 지역의 강수량과, 온도에 대하여 분위사상법(Quantile mapping)과 상세화기법(downscaling)을 적용하였다. GCM 모의자료는 캐나다기후센터(CCCma; Canadian Centre for Climate Modeling and Analysis)의 CGCM2 A2, B2시나리오의 $2001{\sim}2100$년 자료를 사용하였으며, GCM 모의결과값과 국내관측값과의 계통적오차(systematic bias)를 보정하기 위하여 분위사상법을 적용하였다. 강수자료의 경우 한반도의 강수특성을 반영하기 위하여 홍수기, 비홍수기로 구분지어 감마분포를 이용하였고, 온도자료의 경우 계절적 특성을 반영하기 위하여 봄/가을, 여름, 겨울로 구분지어 표준정규분포를 이용하여 분위사상법을 적용하였다. 강수자료의 경우 과거($1965{\sim}1989$:25개년)의 31개소의 일평균강우 자료를, 온도자료의 경우 과거($1965{\sim}1989$)의 11개소의 일평균온도 자료를 사용하였다. 이러한 분위사상법의 적용으로 GCM 모의결과값과 관측값사이의 계통적오차를 보정하였으며, 그 결과 강수자료의 홍수기의 경우 모의결과값과 관측값의 차이가 3.79mm/day에서 0.62mm/day로, 비홍수기의 경우 0.24mm/day에서 0.02mm/day로 각각 83%, 92% 보정된것을 확인하였으며, 각각의 확률분포 매개변수를 추출하였다. Random Cascade 모형의 자기유사성 및 무작위 변동성계수를 추정하기 위하여 2002년 8월 6일 00:10부터 8월 9일 24:00까지 432장의 레이더 스캔을 사용하여 스케일분석을 실시하였으며, 모형적용결과 연평균 강우량의 변화는 A2의 경우 797.89mm에서 1297.09mm로 B2의 경우 815.02mm에서 1383.93mm로 나타났다.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.5 no.3
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• pp.186-194
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• 2000

In this study, the oceanic responses to given atmospheric boundary conditions are investigated using a mesoscale ocean circulation model. The numerical experiments are divided into two parts: One is, so called, spin-up experiment and the other is reproduction experiment. The spin-up experiment simulates climatic state of ocean by integrating the ocean model with upper boundary conditions of the monthly mean atmospheric climate data. In the reproduction experiment, for the reproduction of major oceanic changes around Korean Peninsula during the period of 1980-1998 (19 years), the model has been integrated under the boundary condition of the 19year monthly mean atmosphere data. The spined-up state of ocean generated from the spin-up experiment is assigned to the initial boundary condition of the reproduction experiment. In the spin-up experiment, the model properly simulates the major features of circulation structure around Korean Peninsula; such as separation of East Korean Warm Current (EKWC), formation of the polar front, cold water band associated with the small scale eddies in the East Sea, the formation of front along west coast, and the seasonal variation of circulation pattern caused by changing upwind current in the West Sea. In the reproduction experiment, the model has shown the interannual sea surface temperature variations and a warming trend of about 0.5$^{\circ}$C during the period around Korean Peninsula, as in the case of the observation. Therefore, it is concluded that the model is capable of simulating not only the mean states but also the variabilities of ocean under the given atmosphere boundary conditions.

• Journal of Korea Water Resources Association
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• v.34 no.4
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• pp.335-345
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• 2001

The objective of this research is to analyze the hydrological environment changes in Daechung Dam Basin due to the global warming. GCM simulation results are used to predict the possible changes in precipitation and temperature. The changes of potential evapotranspiration, soil moisture and runoff due to the changes of precipitation and temperature are analyzed using a conceptual water balance model. From the simulation results using the water balance model for lx$CO_2$ and 2x$CO_2$ situations, it has been found that the runoff would decrease in Winter, but increase in Summer and Fall due to the global warming. Therefore, it is predicted that the frequency of drought and flood occurrences in Daechung Dam Basin would be increased in 2x$CO_2$ condition.

• Journal of the Korean earth science society
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• v.28 no.2
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• pp.214-226
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• 2007

Because precipitation is influenced by various atmospheric variables, it is highly nonlinear. Although precipitation predicted by a dynamic model can be corrected by using a nonlinear Artificial Neural Network, this approach has limits such as choices of the initial weight, local minima and the number of neurons, etc. In the present paper, we correct simulated precipitation by using a multiple linear regression (MLR) method, which is simple and widely used. First of all, Ensemble hindcast is conducted by the PNU/CME Coupled General Circulation Model (CGCM) (Park and Ahn, 2004) for the period from April to August in 1979-2005. MLR is applied to precipitation simulated by PNU/CME CGCM for the months of June (lead 2), July (lead 3), August (lead 4) and seasonal mean JJA (from June to August) of the Northeast Asian region including the Korean Peninsula $(110^{\circ}-145^{\circ}E,\;25-55^{\circ}N)$. We build the MLR model using a linear relationship between observed precipitation and the hindcasted results from the PNU/CME CGCM. The predictor variables selected from CGCM are precipitation, 500 hPa vertical velocity, 200 hPa divergence, surface air temperature and others. After performing a leave-oneout cross validation, the results are compared with the PNU/CME CGCM's. The results including Heidke skill scores demonstrate that the MLR corrected results have better forecasts than the direct CGCM result for rainfall.