• 한국수자원학회논문집
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• 제45권2호
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• pp.165-178
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• 2012

본 연구에서는 지표수문해석모형을 활용한 동아시아 지역의 유출해석을 수행하고 그 적용성을 평가하였다. 이에 전지구자료를 수집한 후 모형의 입력자료로 재구성하였으며, 모의 결과의 검증을 위해 GRDC에서 제공하는 국외 34개 지점의 관측유량자료를 수집하였다. 쾨펜의 기후대 구분을 통한 매개변수 전이 방법을 이용하여 미계측지역의 유출 매개변수를 결정하였으며, 동아시아지역에 유출해석을 수행하였다. 그 결과 미계측지역으로 가정한 17개 유역에서 모의치가 관측치와 유사하게 거동하는 것으로 나타나 결과의 신뢰성이 높음을 확인하였다. 최종 결정된 매개변수로부터 동아시아 전역에 수문성분을 산정하였으며, 대체로 동아시아 지역의 국가들의 수문성분 거동은 계절별로 유사한 것으로 확인되었다. 또한, 중국의 남부지역, 일본 및 대만은 동아시아 내에서도 유출의 발생이 가장 높은 반면, 몽골 및 중국 북부지역에서는 매우 낮은 것으로 분석되었다.

• 한국지구과학회지
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• 제32권7호
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• pp.750-760
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• 2011

본 연구에서는 신뢰성 있는 국가표준 지역기후변화 시나리오 생산을 위해 현재기후에 대한 SNURCM과 WRF의 재현성을 검증하였다. 국립기상연구소에서 생산된 HadGEM2-AO 전구자료를 지역기후모형의 경계조건으로 사용하여 CORDEX 규준 하에 28년(1978-2005)간의 장기적분을 수행하였다. 두 모형은 연평균 지표 온도 분포를 관측과의 공간상관계수가 0.98 이상으로 매우 높은 일치성을 나타내었지만, 모형 영역의 북쪽 경계를 중심으로 한랭 편차를 공통적으로 보였다. 강수의 경우 또한 육지 지역을 대상으로 한 관측과의 공간 상관 계수는 SNURCM이 0.85, WRF가 0.79로 나타나 우수한 모의 결과를 보였다. 두 모형에서 모의된 강수 분포는 적도와 중위도 지역 간에 상반되는 특성을 보였다. SNURCM은 WRF에 비교하여 중위도 동아시아 몬순 강수대의 분포를 적도 지역의 강수대보다 상대적으로 잘 모의하였으나, WRF는 그 반대의 결과를 나타내었다. 여름철(JJA) 보다 봄철(MAM)에 과다 모의되었지만 모의된 강수 분포의 일치성은 봄철에 높게 나타났다. 세부영역 별 분석에서 두 모형은 7월 강수 최대 시점과 양을 비교적 정확히 모의하였고, 특히 내륙 지역 강수량의 모의 정확도가 해양에 영향 받는 지역보다 높았다. 모의결과는 한반도 상의 높은 일평균 지표온도일수와 강한 강수일수를 표현하는데 한계를 보였다.

• 한국농림기상학회:학술대회논문집
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• 한국농림기상학회 2011년도 학술발표회
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• pp.20-27
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• 2011

A system for fine-resolution long-range weather forecast is introduced in this study. The system is basically consisted of a global-scale coupled general circulation model (CGCM) and Weather Research and Forecast (WRF) regional model. The system makes use of a data assimilation method in order to reduce the initial shock or drift that occurs at the beginning of coupling due to imbalance between model dynamics and observed initial condition. The long-range predictions are produced in the system based on a non-linear ensemble method. At the same time, the model bias are eliminated by estimating the difference between hindcast model climate and observation. In this research, the predictability of the forecast system is studied, and it is illustrated that the system can be effectively used for the high resolution long-term weather prediction. Also, using the system, fine-resolution climatological data has been produced with high degree of accuracy. It is proved that the production of agrometeorological variables that are not intensively observed are also possible.

• 한국농공학회논문집
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• 제51권5호
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• pp.25-34
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• 2009

The objective of this study is to evaluate the future potential climate and vegetation canopy change impact on a dam watershed hydrology. A $6,661.5\;km^2$ dam watershed, the part of Han-river basin which has the watershed outlet at Chungju dam was selected. The SWAT model was calibrated and verified using 9 year and another 7 year daily dam inflow data. The Nash-Sutcliffe model efficiency ranged from 0.43 to 0.91. The Canadian Centre for Climate Modelling and Analysis (CCCma) Coupled Global Climate Model3 (CGCM3) data based on Intergovernmental Panel on Climate Change (IPCC) SRES (Special Report Emission Scenarios) B1 scenario was adopted for future climate condition and the data were downscaled by artificial neural network method. The future vegetation canopy condition was predicted by using nonlinear regression between monthly LAI (Leaf Area Index) of each land cover from MODIS satellite image and monthly mean temperature was accomplished. The future watershed mean temperatures of 2100 increased by $2.0^{\circ}C$, and the precipitation increased by 20.4 % based on 2001 data. The vegetation canopy prediction results showed that the 2100 year LAI of deciduous, evergreen and mixed on April increased 57.1 %, 15.5 %, and 62.5% respectively. The 2100 evapotranspiration, dam inflow, soil moisture content and groundwater recharge increased 10.2 %, 38.1 %, 16.6 %, and 118.9 % respectively. The consideration of future vegetation canopy affected up to 3.0%, 1.3%, 4.2%, and 3.6% respectively for each component.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2005년도 학술발표회 논문집
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• pp.143-148
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• 2005

The main purpose of this study is to suggest and evaluate an operational method for assessing the potential impact of climate change on hydrologic components and water resources of regional scale river basins. The method, which uses large scale climate change information provided by a state of the art general circulation model(GCM) comprises a statistical downscaling approach and a spatially distributed hydrological model applied to a river basin located in Korea. First, we construct global climate change scenarios using the YONU GCM control run and transient experiments, then transform the YONU GCM grid-box predictions with coarse resolution of climate change into the site-specific values by statistical downscaling techniques. The values are used to modify the parameters of the stochastic weather generator model for the simulation of the site-specific daily weather time series. The weather series fed into a semi-distributed hydrological model called SLURP to simulate the streamflows associated with other water resources for the condition of $2CO_2$. This approach is applied to the Yongdam dam basin in southern part of Korea. The results show that under the condition of $2CO_2$, about $7.6\% of annual mean streamflow is reduced when it is compared with the observed one. And while Seasonal streamflows in the winter and autumn are increased, a streamflow in the summer is decreased. However, the seasonality of the simulated series is similar to the observed pattern and the analysis of the duration cure shows the mean of averaged low flow is increased while the averaged wet and normal flow are decreased for the climate change.

• 한국물환경학회지
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• 제25권6호
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• pp.821-831
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• 2009

The study was aimed to assess the expected impact of climate change on the water cycle and soil losses in Daecheong Reservoir watershed, Korea using the Soil and Water Assessment Tool (SWAT) that was validated for the watershed in a previous study. Future climate data including precipitation, temperature and humidity generated by introducing a regional climate model (Mesoscale Model Version 5, MM5) to dynamically downscale global circulation model (European Centre Hamburg Model Version 4, ECHAM4) were used to simulate the hydrological responses and soil erosion processes in the future 100 years (2001~2100) under the Special Report on Emissions Scenario (SRES) A1B. The results indicated that the climate change may increase in the amount of surface runoff and thereby sediment load to the reservoir. Spatially, the impact was relatively more significant in the subbasin Bocheongcheon because of its lower occupation rate of forest land compared to other subbasins. Seasonally, the increase of surface runoff and soil losses was more significant during late summer and fall season when both flood control and turbidity flow control are necessary for the reservoir and downstream. The occurrence of extreme turbidity flow events during these period is more vulnerable to reservoir operation because the suspended solids that remained water column can be resuspended by vertical mixing during winter turnover period. The study results provide useful information for the development of adaptive management strategy for the reservoir to cope with the expected impact of future climate change.

• 한국농공학회논문집
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• 제55권4호
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• pp.95-106
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• 2013

It is now generally known that dynamical climate modeling outputs include systematic biases in reproducing the properties of atmospheric variables such as, preciptation and temerature. There is thus, general consensus among the researchers about the need of bias-correction process prior to using climate model results especially for hydrologic applications. Among the number of bias-correction methods, distribution (e.g., cumulative distribution fuction, CDF) mapping based approach has been evaluated as one of the skillful techniques. This study investigates the uncertainty of using various CDF mapping-based methods for bias-correciton in assessing regional climate change Impacts. Two different dynamicailly-downscaled Global Circulation Model results (CCSM and GFDL under ARES4 A2 scenario) using Regional Spectial Model for retrospective peiod (1969-2000) and future period (2039-2069) were collected over the west central Florida. Total 12 possible methods (i.e., 3 for developing distribution by each of 4 for estimating biases in future projections) were examined and the variations among the results using different methods were evaluated in various ways. The results for daily temperature showed that while mean and standard deviation of Tmax and Tmin has relatively small variation among the bias-correction methods, monthly maximum values showed as significant variation (~2'C) as the mean differences between the retrospective simulations and future projections. The accuracy of raw preciptiation predictions was much worse than temerature and bias-corrected results appreared to be more significantly influenced by the methodologies. Furthermore the uncertainty of bias-correction was found to be relevant to the performance of climate model (i.e., CCSM results which showed relatively worse accuracy showed larger variation among the bias-correction methods). Concludingly bias-correction methodology is an important sourse of uncertainty among other processes that may be required for cliamte change impact assessment. This study underscores the need to carefully select a bias-correction method and that the approach for any given analysis should depend on the research question being asked.

• 한국제4기학회:학술대회논문집
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• 한국제4기학회 2004년도 추계학술대회
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• pp.37-43
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• 2004

The response of the CCCma coupled climate model to the imposition of LGM conditions is investigated. The global mean SAT and SST decrease by about $10^{\circ}C$ and $5.6^{\circ}C$ in the coupled model. Tropical SST decreases by $6.5^{\circ}C$, whereas CLIMAP reconstructions suggest that the tropics cool by only about $1.7^{\circ}C$, although the larger tropical cooling is consistent with the more recent proxy estimates. With the incorporation of a full ocean component, the coupled model gives a realistic spatial SST pattern, capturing features associated with ocean dynamics that are seen in the CLIMAP reconstructions. The larger decrease of the surface temperature in the model is associated with a reduction in global precipitation rate (about 15%). The tropical Pacific warm pool retreats to the west and a mean La $Ni\tilde{n}a$-like response is simulated with less precipitation over the central Pacific and more in the western tropical Pacific. The more arid ocean climate in the LGM results in an increase in SSS almost everywhere. This is particularly the case in the Arctic Ocean where large SSS increase is due to a decrease in river discharge to the Arctic Ocean associated with the accumulation of snow over the ice sheet, but in the North Atlantic by contrast SSS decreases markedly. This remarkable reduction of SSS in the North Atlantic is attributed to an increase in fresh water supply by an increase in discharges from the Mississippi and Amazon rivers and an increase in P-E over the North Atlantic ocean itself. The discharges increase in association with the wetter LGM climate south of the Laurentide ice sheet and in South America. The fresh water capping of the northern North Atlantic results in a marked reduction of deep convection and consequently a marked weakening of the North Atlantic overturning circulation. In the LGM, the maximum overturning stream function associated with the NADW formation decreases by about 60% relative to the control run, while in the Southern Ocean, oceanic convection is stronger in the LGM due to reduced stratification associated with an increase in SSS and a decrease in SST and the overturning stream function associated with the formation of AABW and the outflow increases substantially.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2012년도 학술발표회
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• pp.363-363
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• 2012

최근 극심하게 변화하고 있는 기후에 적응하기 위해서 미래 기후를 좀 더 정확하게 예측하고자 많은 연구가 진행되어지고 있다. 결국, 기후변화에 따른 기온, 강수, 습도, 바람 등의 기후정보를 기후모형을 이용하여 얻게 되면 이에 따라 우리가 받게 되는 영향, 취약성 등을 평가하여 다양하게 활용하고자 하는 것이다. 우리나라는 지형적으로 육지의 70% 정도를 산악 지역이 차지할 만큼 복잡한 지형과 다양한 기후의 특성을 나타나고 있어 미래에 대한 기후변화 시나리오를 산출하는 기본적인 도구이면서 공간해상도가 약 400km인 전지구 기후모형(Global Climate Model; GCM)으로 그대로 활용하기에는 곤란하다. 따라서 지역기후모형(Regional Climate Model; RCM)을 통해서 추정된 A1B시나리오를 기본 기후변화 시나리오로 활용하는 것이 일반적이다. 하지만 GCM이나 RCM 기반 기후변화 시나리오는 실제 강수의 특성을 제대로 재현하지 못하는 경향이 있으며 이러한 문제점을 개선하기 위해서 통계적인 상세화 기법을 통해서 수문학적으로 활용 가능한 기후변화 시나리오를 생산하여 이용한다. 본 연구에서는 새롭게 제공되는 RCP시나리오를 이용하여 북한을 포함하는 한반도 전체에 대한 기후변화 영향을 평가하고자 한다.

• 한국시스템다이내믹스연구
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• 제10권3호
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• pp.105-124
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• 2009

The situation of the global food markets has been being rapidly restructured and entering on a new phase by new dynamic and driving forces. The factors such as economic growth and income increase, high energy price, globalization, urbanization, and global climate change are transforming patterns of food consumption, production, and markets. The prices and markets of world food and energy are getting increasingly linked each other. Food and fuel are the global dilemma issues associated with the risk of diverting farmland or of consuming cereals for biofuel production in detriment of the cereals supply to the global food markets. An estimated 100 million tons of grain per year are being redirected from food to fuel. Therefore, the objectives of this study are as follows: Firstly, the study examines situations of the world food and energy resources, analyzes the trends of prices of the crude oil and biofuel, and formulates the food-energy links mechanism. Secondly, the study builds a simulation model, based on system dynamics approach, for not only analyzing the global cereals market and energy market but also forecasting the global production, consumption, and stock of those markets by 2030 in the future. The model of this study consists of four sectors, i.e., world population dynamics sector, global food market dynamics sector, global energy market dynamics sector, scenario sector of world economic growth and oil price.