• 한국물환경학회지
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• 제36권1호
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• pp.14-28
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• 2020

Future climate change may affect the hydro-thermal and biogeochemical characteristics of dam reservoirs, the most important water resources in Korea. Thus, scientific projection of the impact of climate change on the reservoir environment, factoring uncertainties, is crucial for sustainable water use. The purpose of this study was to predict the future water temperature and stratification structure of the Soyanggang Reservoir in response to a total of 42 scenarios, combining two climate scenarios, seven GCM models, one surface runoff model, and three wind scenarios of hydrodynamic model, and to quantify the uncertainty of each modeling step and scenario. Although there are differences depending on the scenarios, the annual reservoir water temperature tended to rise steadily. In the RCP 4.5 and 8.5 scenarios, the upper water temperature is expected to rise by 0.029 ℃ (±0.012)/year and 0.048 ℃ (±0.014)/year, respectively. These rise rates are correspond to 88.1 % and 85.7 % of the air temperature rise rate. Meanwhile, the lower water temperature is expected to rise by 0.016 ℃ (±0.009)/year and 0.027 ℃ (±0.010)/year, respectively, which is approximately 48.6 % and 46.3 % of the air temperature rise rate. Additionally, as the water temperatures rises, the stratification strength of the reservoir is expected to be stronger, and the number of days when the temperature difference between the upper and lower layers exceeds 5 ℃ increases in the future. As a result of uncertainty quantification, the uncertainty of the GCM models showed the highest contribution with 55.8 %, followed by 30.8 % RCP scenario, and 12.8 % W2 model.

• 한국수자원학회논문집
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• 제46권8호
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• pp.833-842
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• 2013

분위사상법(QM, Quantile Mapping)은GCM(Global Climate Model) 자료의 계통적 오차를 보정하여 보다 신뢰성 높은 자료로 재생성하기 위해 활용되고 있다. 이 기법은 사상(mapping)시키려는 대상(object) 자료의 통계분포모수가 정상적(stationarity)이라는 가정 하에 대상 자료의 누적확률분포(CDF, Cumulative Distribution Function)를 목표(target) CDF에 통계적으로 투영시키는 것이 일반적이다. 따라서 GCM에서 제공되는 미래 기후시나리오의 강우시계열과 같이 비정상성(non-stationarity)을 갖는 장기 시계열자료에 대한 적용에는 문제점을 보이고 있다. 본 연구에서는 비정상성을 갖는 장기시계열자료의 오차보정을 위해 통계분포모수에 경향성을 부여하는 비정상성 분위사상법(NSQM, Nonstationary Quantile Mapping)을 적용하였다. NSQM 적용을 위한 확률분포로 수문분야에서 광범위하게 쓰이고 있는Gamma 분포를 선정하였으며, 대상 시나리오는 CCCma (Canadian Centre for Climate modeling and analysis)에서 제공하고 있는 CGCM3.1/T63모형의 20C3M(reference scenario)과 SRES A2 시나리오(projection scenario)를 활용하였다. 한강유역 내 관측기간이 충분한 10개의 지상관측소로부터 강우량을 수집하였다. 또한 6월과 10월사이에 연 강수량의 65% 이상이 집중되는 한반도의 계절성을 반영하기 위해 홍수기(6~10월)와 비홍수기(11~5월)를 구분하였고, 기준기간(Baseline)은 1973~2000년, 전망기간(Projection)은 2011~2100년으로 구분하였다. 다양한 목표분포의 설정을 통하여 NSQM의 적용성을 평가하고자 하였으며, 전망기간은 FF시나리오(Foreseeable Future Scenario, 2011~2040년), MF시나리오(Mid-term Future Scenario, 2041~2070년), LF시나리오(Long-term Future Scenario, 2071~2100년)의 3개의 구간으로 설정하여 기준기간과 전망기간의 연평균 강우량에 대한 경향성분석을 실시하였다. 그 결과NSQM이 FF시나리오에서 330.1mm(25.2%), MF시나리오에서 564.5mm(43.1%), LF시나리오에서 634.3mm(48.5%)로 증가하는 전망결과를 나타내고 있었다. 정상성기법을 적용한 결과, 전망기간 중 전체적으로는 동일한 평균값을 갖는 목표통계모수를 사용한다고 하여도, 전망전반부에서 과다하고, 후반부에서 오히려 과소한 전망을 보여주고 있었다. 이러한 결과는 비정상성기법을 사용함으로써 상당부분 개선될 수 있음을 확인하였다.

• 응용통계연구
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• 제33권2호
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• pp.185-201
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• 2020

예전부터 시나리오 인구추계(scenario population projection)는 미래 실현개연성이 높은 상황 반영과 통계적 음해석 용이성으로 각광을 받아왔다. 통계청 (2019)도 특별 시나리오를 포함한 30가지 조합 결과를 공식통계로 제시하고 있다. 하지만, 이런 결정론적(determinant) 인구추계는 미래의 불확실성(uncertainty)에 대해 제한적으로 정보를 제공하고, 시나리오 기반 예측치이므로 확률적이지 않으며, 시간에 따라 인구변동 3요소(출산, 사망, 이동)들의 완벽한 자기상관을 보이는 등 여러 한계점이 있다. 따라서 국제기구 UN, 독일 막스플랑크 인구연구소(MPIDR), 오스트리아 비엔나인구연구소(VID) 등은 확률론적(stochastic) 기반 인구추계를 제시하고 있다. 더불어 해외 일부 국가 통계청에서도 이 방식을 도입해 시나리오 결과와 함께 정보를 제공하고 있다. 본 논문은 우리나라의 인구추계를 확률론적 기반으로 산출한 후, 시나리오(결정론적) 인구추계 결과와 비교해 장·단점과 시사점을 도출해본다.

• 대기
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• 제26권3호
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• pp.373-386
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• 2016

The future variability of Wind Energy Density (WED) over the Korean Peninsula under RCP climate change scenario is projected using ensemble analysis. As for the projection of the future WED, changes between the historical period (1981~2005) and the future projection (2021~2050) are examined by analyzing annual and seasonal mean, and Coefficient of Variation (CV) of WED. The annual mean of WED in the future is expected to decrease compared to the past ones in RCP 4.5 and RCP 8.5 respectively. However, the CV is expected to increase in RCP 8.5. WEDs in spring and summer are expected to increase in both scenarios RCP 4.5 and RCP 8.5. In particular, it is predicted that the variation of CV for WED in winter is larger than other seasons. The time series of WED for three major wind farms in Korea exhibit a decrease trend over the future period (2021~2050) in Gochang for autumn, in Daegwanryeong for spring, and in Jeju for autumn. Through analyses of the relationship between changes in wind energy and pressure gradients, the fact that changes in pressure gradients would affect changes in WED is identified. Our results can be used as a background data for devising a plan to develop and operate wind farm over the Korean Peninsula.

• 대기
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• 제17권1호
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• pp.55-68
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• 2007

Future climate changes over East Asia are projected by anthropogenic forcing of greenhouse gases and aerosols using ECHO-G/S (ECHAM4/HOPE-G). Climate simulation in the 21st century is conducted with three standard SRES scenarios (A1B, B1, and A2) and the model performance is assessed by the 20th Century (20C3M) experiment. From the present climate simulation (20C3M), the model reproduced reliable climate state in the most fields, however, cold bias in temperature and dry bias of summer in precipitation occurred. The intercomparison among models using Taylor diagram indicates that ECHO-G/S exhibits smaller mean bias and higher pattern correlation than other nine AOGCMs. Based on SRES scenarios, East Asia will experience warmer and wetter climate in the coming 21st century. Changes of geographical patterns from the present to the future are considerably similar through all the scenarios except for the magnitude difference. The temperature in winter and precipitation in summer show remarkable increase. In spite of the large uncertainty in simulating precipitation by regional scale, we found that the summer (winter) precipitation at eastern coast (north of $40^{\circ}N$) of East Asia has significantly increased. In the 21st century, the warming over the continents of East Asia showed much more increase than that over the ocean. Hence, more enhanced (weakened) land-sea thermal contrast over East Asia in summer (winter) will cause strong (weak) monsoon. In summer, the low pressure located in East Asia becomes deeper and the moisture from the south or southeast is transported more into the land. These result in increasing precipitation amount over East Asia, especially at the coastal region. In winter, the increase (decrease) of precipitation is accompanied by strengthening (weakening) of baroclinicity over the land (sea) of East Asia.

• 대기
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• 제29권5호
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• pp.585-597
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• 2019

This study evaluates the performance of Weather Research and Forecasting (WRF) model in simulating temperature over the COordinated Regional climate Downscaling EXperiment-East Asia (CORDEX-EA) Phase 2 domain for the reference period (1981~2005), and assesses the changes in temperature and its extremes in the mid-21st century (2026~2050) under global warming based on Representative Concentration Pathway (RCP) scenarios. MPI-ESM-LR forced by two RCP scenarios (RCP2.6 and RCP8.5) is used as initial and lateral boundary conditions. Overall, WRF can capture the observed features of temperature distribution reflecting local topographic characteristic, despite some disagreement between the observed and simulated patterns. Basically, WRF shows a systematic cold bias in daily mean, minimum and maximum temperature over the entire domain. According to the future projections, summer and winter mean temperatures over East Asia will significantly increase in the mid-21st century. The mean temperature rise is expected to be greater in winter than in summer. In accordance with these results, summer (winter) is projected to begin earlier (later) in the future compared to the historical period. Furthermore, a rise in extreme temperatures shows a tendency to be greater in the future. The averages of daily minimum and maximum temperatures above 90 percentiles are likely to be intensified in the high-latitude, while hot days and hot nights tend to be more frequent in the low-latitude in the mid-21st century. Especially, East Asia would be suffered from strong increases in nocturnal temperature under future global warming.

• 한국농공학회논문집
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• 제56권4호
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• pp.59-68
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• 2014

Climate change influences multiple environmental aspects, certain of which are specifically related to agricultural water resources such as water supply, water management, droughts and floods. Understanding the impact of climate change on reservoirs in relation to the passage of time is an important component of water resource management for stable water supply maintenance. Changes on rainfall and hydrologic patterns due to climate change can increases the occurrence of reservoir water shortage and affect the future availability of agricultural water resources. It is a main concern for sustainable development in agricultural water resources management to evaluate adaptation capability of water supply under the future climate conditions. The purpose of this study is to predict the sustainability of agricultural water demand and supply under future climate change by applying an irrigation vulnerability assessment model to investigate evidence of climate change occurrences at a local scale with respect to potential water supply capacity and irrigation water requirement. Thus, it is a recommended practice in the development of water supply management strategies on reservoir operation under climate change.

• 한국농공학회논문집
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• 제52권4호
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• pp.83-91
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• 2010

Generally, the GCM (General Circulation Model) data by IPCC climate change scenarios are used for future weather prediction. IPCC GCM models predict well for the continental scale, but is not good for the regional scale. This paper tried to generate future temperature and precipitation of 8 scattered meteorological stations in South Korea by using the MIROC3.2 hires GCM data and applying LARS-WG downscaling method. The MIROC3.2 A1B scenario data were adopted because it has the similar pattern comparing with the observed data (1977-2006) among the scenarios. The results showed that both the future precipitation and temperature increased. The 2080s annual temperature increased $3.8{\sim}5.0^{\circ}C$. Especially the future temperature increased up to $4.5{\sim}7.8^{\circ}C$ in winter period (December-February). The future annual precipitation of 2020s, 2050s, and 2080s increased 17.5 %, 27.5 %, and 39.0 % respectively. From the trend analysis for the future projected results, the above middle region of South Korea showed a statistical significance for winter precipitation and south region for summer rainfall.

• 대기
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• 제23권3호
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• pp.347-356
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• 2013

The climate projection with a high spatial resolution is required for the studies on regional climate changes. The Korea Meteorological Administration (KMA) has provided downscaled RCP (Representative Concentration Pathway) scenarios over Korea with 1 km spatial resolution. If there are additional climate projections produced by dynamically downscale, the quality of impacts and vulnerability assessments of Korea would be improved with uncertainty information. This technical note intends to instruct the methods to downscale the climate projections dynamically from the Community Earth System Model (CESM) to the Weather Research and Forecast (WRF) model. In particular, here we focus on the instruction to utilize CAM2WRF, a sub-program to link output of CESM to initial and boundary condition of WRF at Linux platform. We also provide the example of the dynamically downscaled results over Korean Peninsula with 50 km spatial resolution for August, 2020. This instruction can be helpful to utilize global scale climate scenarios for studying regional climate change over Korean peninsula with further validation and uncertainty/bias analysis.

• 한국수자원학회논문집
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• 제51권spc1호
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• pp.1079-1089
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• 2018

기존 기후변화 영향평가에서 발생하는 불확실성에 대한 연구들은 전체과정에서 총 불확실성과 그 전파에 대한 것보다 각 단계별 불확실성에 초점을 맞추어 연구가 진행되었다. 따라서 본 연구에서는 first-order Taylor series expansion에 기반하여 전망의 분산을 이용하는 Uncertainty Delta Method (UDM)를 제안하였으며, 이 방법은 각 단계별 불확실성 정량화와 증감정도, 단계별 불확실성 비율, 총 불확실성의 전파 과정 제시가 가능하다. 본 연구에서는 기후변화 영향평가 과정의 단계별 불확실성 정량화와 전파과정 분석을 위해 미래 2030년부터 2059년까지를 대상으로 2개 배출 시나리오, 3개 GCM, 2개 상세화기법, 2개 수문모형을 사용하였다. 결과를 분석하면, UDM을 이용한 총 불확실성은 5.45(배출시나리오: 4.45, 상세화기법: 0.45, 상세화기법: 0.27, 수문모형: 0.28)이며, 배출 시나리오의 불확실성(4.45)이 가장 크게 나타났다. 불확실성은 각 단계를 거칠수록 증가하는 것으로 나타났다. 이러한 결과는 어떠한 배출시나리오를 선정하느냐에 따라 미래 수자원전망이 매우 달라질 수 있음을 의미한다. 다음으로 Hawkins and Sutton (2009)가 제안한 Fractional Uncertainty Method (FUM)을 이용한 기후변화 영향평가 불확실성 분석에서 가장 불확실성이 큰 요인은 배출 시나리오(FUM 불확실성: 0.52)이며, 이 결과는 UDM 결과와 동일하게 나타났다. 따라서 이 연구에서 제안한 UDM은 기후변화 영향평가에서의 불확실성 이해와 적합한 분석 및 미래 기후변화 대비 보다 나은 수자원 전망이 가능하도록 기여할 것으로 판단된다.