• Title/Summary/Keyword: RegCM4

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Future Projection and Uncertainty Analysis of Low Flow on Climate Change in Dam Basins (기후변화에 따른 저유량 전망 및 불확실성 분석)

  • Lee, Moon Hwan;Bae, Deg Hyo
    • Journal of Climate Change Research
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    • v.7 no.4
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    • pp.407-419
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    • 2016
  • The low flow is the necessary and important index to establish national water planning, however there are lots of uncertainty in the low flow estimation. Therefore, the objectives of this study are to assess the climate change uncertainty and the effects of hydrological models on low flow estimation. The 5 RCMs (HadGEM3-RA, RegCM4, MM5, WRF, and RSM), 5 statistical post-processing methods and 2 hydrological models were applied for evaluation. The study area were selected as Chungju dam and Soyang river dam basin, and the 30 days minimum flow is used for the low flow evaluation. The results of the uncertainty analysis showed that the hydrological model was the largest source of uncertainty about 41.5% in the low flow projection. The uncertainty of hydrological model is higher than the other steps (RCM, statistical post-processing). Also, VIC model is more sensitive for climate change compared to SWAT model. Therefore, the hydrological model should be thoroughly reviewed for the climate change impact assessment on low flow.

Regional Frequency Analysis for Rainfall Under Climate Change (기후변화를 고려한 일강우량의 지역빈도해석)

  • Song, Chang Woo;Kim, Yon Soo;Kang, Na Rae;Lee, Dong Ryul;Kim, Hung Soo
    • Journal of Wetlands Research
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    • v.15 no.1
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    • pp.125-137
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    • 2013
  • Global warming and climate change have influence on abnormal weather pattern and the rainstorm has a localized and intensive tendency in Korea. IPCC(2007) also reported the rainstorm and typhoon will be more and more stronger due to temperature increase during the 21st century. Flood Estimation Handbook(Institute of Hydrology, 1999) published in United Kingdom, in the case that the data period is shorter than return period, recommends the regional frequency analysis rather than point frequency analysis. This study uses Regional Climate Model(RCM) of Korea Meteorological Administration(KMA) for obtaining the rainfall and for performing the regional frequency analysis. We used the rainfall data from 58 stations managed by KMA and used L-moment algorithm suggested by Hosking and wallis(1993) for the regional frequency analysis considering the climate change. As the results, in most stations, the rainfall amounts in frequencies have an increasing tendency except for some stations. According to the A1B scenario, design rainfall is increased by 7~10% compared with the reference period(1970-2010).

Correction of Mean and Extreme Temperature Simulation over South Korea Using a Trend-preserving Bias Correction Method (변동경향을 보존하는 편의보정기법을 이용한 우리나라의 평균 및 극한기온 모의결과 보정)

  • Jung, Hyun-Chae;Suh, Myoung-Seok
    • Atmosphere
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    • v.25 no.2
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    • pp.205-219
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    • 2015
  • In this study, the simulation results of temperature by regional climate model (Reg- CM4) over South Korea were corrected by Hempel et al. (2013)'s method (Hempel method), and evaluated with the observation data of 50 stations from Korea Meteorological Administration. Among the 30 years (1981~2010) of simulation data, 20 years (1981~2000) of simulation data were used as a training data, and the remnant 10 years (2001~2010) data were used for the evaluation of correction. In general, the Hempel method and parametric quantile mapping show a reasonable correction both in mean and extreme climate of temperature. As the results, the systematic underestimation of mean temperature was greatly reduced after bias correction by Hempel method. And the overestimation of extreme climate, such as the number of TN5% and freezing day, was significantly recovered. In addition to that, the Hempel method better preserved the temporal trend of simulated temperature than other bias correction methods, such as the quantile mapping. However, the overcorrection of the extreme climate related to the upper quantile, such as TX5% and hot days, resulted in the exaggeration of the simulation errors. In general, the Hempel method can reduce the systematic biases embedded in the simulation results preserving the temporal trend but it tends to overcorrect the non-linear biases, in particular, extreme climate related to the upper percentile.

Analysis of Regional Climate Model For Climate Change Impacts on Water Resources (기후변화에 따른 수자원 영향 평가를 위한 Regional Climate Model에 의한 강수 자료의 특성 분석)

  • Kwon, Hyun-Ha;Kim, Byung-Sik;Yoon, Seok-Young;Kim, Bo-Kyung
    • Proceedings of the Korea Water Resources Association Conference
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    • 2008.05a
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    • pp.1018-1022
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    • 2008
  • 2007년 Intergovernmental Panel on Climate Change(IPCC) 4차보고서 이후로 지구 온난화에 대한 다양한 부분에 영향 분석 연구가 더욱 활발하게 진행되고 있으며, 그 가운데 수자원 즉 육상의 물 순환은 인간 활동과 생태계 전반에 대한 직접 영향으로 인해 기후변화 정책 수립 시 그 중요성이 더욱 부각되고 있다. 현재까지, 많은 연구에 있어서 Global Circulation Model (GCM)을 직접 축소기법을 이용한 후 이를 수문 모형에 입력하여 수자원 영향 분석을 실시해오고 있다. 국외를 중심으로 기존 GCM보다 해상도가 높은 Regional Climate Model(RCM)을 이용한 분석이 일부 시행되고 있으나, 국내에서는 자료의 가용 여부 및 적용성의 검토가 아직 미비한 실정이다. 이러한 관점에서 본 연구에서는 27km의 해상도를 갖는 기상청 RegCM3 RCM에서 도출된 10일 간격 기후변화 SRES 시나리오 자료에 대한 적합성을 평가하고자 한다. 적합성을 평가 하기위해서 국내 주요지점에 근접한 격자자료를 RCM으로부터 추출하고 이에 대한 수문학적 특성치 분석, 저빈도 분석(low frequency analysis), 극치사상의 분포형태 등을 실측 강수자료와 다양한 형태로 비교 검토하여 RCM 자료의 적합성을 평가하였다.

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Inter-comparison of Prediction Skills of Multiple Linear Regression Methods Using Monthly Temperature Simulated by Multi-Regional Climate Models (다중 지역기후모델로부터 모의된 월 기온자료를 이용한 다중선형회귀모형들의 예측성능 비교)

  • Seong, Min-Gyu;Kim, Chansoo;Suh, Myoung-Seok
    • Atmosphere
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    • v.25 no.4
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    • pp.669-683
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    • 2015
  • In this study, we investigated the prediction skills of four multiple linear regression methods for monthly air temperature over South Korea. We used simulation results from four regional climate models (RegCM4, SNURCM, WRF, and YSURSM) driven by two boundary conditions (NCEP/DOE Reanalysis 2 and ERA-Interim). We selected 15 years (1989~2003) as the training period and the last 5 years (2004~2008) as validation period. The four regression methods used in this study are as follows: 1) Homogeneous Multiple linear Regression (HMR), 2) Homogeneous Multiple linear Regression constraining the regression coefficients to be nonnegative (HMR+), 3) non-homogeneous multiple linear regression (EMOS; Ensemble Model Output Statistics), 4) EMOS with positive coefficients (EMOS+). It is same method as the third method except for constraining the coefficients to be nonnegative. The four regression methods showed similar prediction skills for the monthly air temperature over South Korea. However, the prediction skills of regression methods which don't constrain regression coefficients to be nonnegative are clearly impacted by the existence of outliers. Among the four multiple linear regression methods, HMR+ and EMOS+ methods showed the best skill during the validation period. HMR+ and EMOS+ methods showed a very similar performance in terms of the MAE and RMSE. Therefore, we recommend the HMR+ as the best method because of ease of development and applications.

Projection of future hydrometeorological change scenarios over Republic of Korea using a dynamical downscaling technique (역학적 상세화 기법을 활용한 우리나라 미래 수문기상변화 시나리오 전망)

  • Shin, Jin-Ho;Lee, Hyo-Shin;Kwon, Won-Tae
    • Proceedings of the Korea Water Resources Association Conference
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    • 2010.05a
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    • pp.258-262
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    • 2010
  • 지역기후모델 RegCM3 이용하여 역학적 상세화 이중둥지격자체계를 구축하고 관측, ECHO-G/S의 20C3M 및 SRES A2 시나리오를 이용하여 동아시아(60km 분해능)와 한반도(20km 분해능)에 대한 현재 및 미래 (1971-2100, 130년)의 기후변화 시나리오 자료를 생산하여 구축하였다. 현재 1971-2000년 기간 동안 상세화된 기온은 관측에 대해 저온 편의와 여름 강수는 건조 편의가 나타나는 계통오차가 있으나, 상세화된 자료는 한반도의 지형적 특성이 잘 반영되었고 관측의 월별, 계절별 변동성을 유사하게 모의하는 등 재분석 자료를 성공적으로 상세화한 것으로 판단된다. 미래 100년(2001-2100년)에 대해 전반기(2021-2050) 및 후반기(2070-2099)의 시나리오기후변동을 분석한 결과, 상세화된 지역별, 계절별, 연도별 기온 상승의 시 공간적 분포를 잘 보여주며, 기온상승(전반기: 동아시아지역~$1.8^{\circ}C$, 남한~$1.6^{\circ}C$, 후반기: 동아시아지역~$4.7^{\circ}C$, 남한~$4.6^{\circ}C$)에 의한 대기 중 수증기 함유량 증가와 여름 몬순의 강화로 전계절에 대해 강수량(전반기: 동아시아~10.5%, 남한~6.7%, 후반기: 동아시아~20.1%, 남한~31.9%)이 증가할 것으로 전망되었다. 수문기상 변화를 살펴보면, 미래 후반기에 남한은 $4.6^{\circ}C$가 상승하여 적설깊이는 5.3mm(-92.3%)가 감소할 것이고, 강수량의 연변동성을 크나 전체적으로 증가할 것이며, 토양수분, 증발산 또한 강수량 증가와 연관되어 증가할 것으로 전망되었다. 이렇게 ECHO-G/S SRES A2 시나리오를 기반으로 하여 역학적으로 상세화된 시나리오는 통계적으로 상세화된 시나리오 결과와 비교 검증함으로써 다중모델기법에 의해 불확실성을 제시함으로써 수문기상변화 예측을 위한 신뢰성 있는 자료로 활용될 수 있을 것으로 판단된다.

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Design and deposition of two-layer antireflection and antistatic coatings using a TiN thin film (TiN 박막을 이용한 2층 무반사 코팅의 설계 및 층착)

  • 황보창권
    • Korean Journal of Optics and Photonics
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    • v.11 no.5
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    • pp.323-329
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    • 2000
  • In this study we have calculated an ideal complex refractive index of a TiN trim used in a layer of anl1reilecnon (I\R) coatmg, [air$ISiO_2ITiNIglass$] in the visible. Also we simulated the rellectance of lwo-layer AR coating by varying the thicknesses of TiN and $SiO_2$ layers, respecl1vely. The simolation results show that we can controllhe lowest reflectance and AR band of tile AR coating. The TIN fihns were fabricated by a RF magnetron sputtering apparalus. The chemical, structural and electrical properties of TiN fih11S were inveshgated by the Rutherford backscattering spech'oscopy (RBS), atomic force microscope (AFM) and 4-point probe. The optical properlies were inve,tigated by the spectrophotometer and vanable angle spectroscopic ellipsometer (VASE). The smface roughness of TiN flhns \vas $9~10\AA$. TIle resistivity of TiN films was TEX>$360~730\mu$\Omega $ cm. The ,toichlOllletry of TiN film was 1'1: O:N = I: 0.65 :0.95 and ilic oxygen wa~ found on ilie smface. With these experimental and simu]al1on resulLs, we deposited duo: two-layer AR coating, [air$ISiO_2ITiNIglass$] and the refleClance was under 0.5% ill the regIOn of 440-650 run. 0 run.

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Predicting the Potential Distribution of Korean Pine (Pinus koraiensis) Using an Ensemble of Climate Scenarios (앙상블 기후 시나리오 자료를 활용한 우리나라 잣나무림 분포 적지 전망)

  • Kim, Jaeuk;Jung, Huicheul;Jeon, Seong Woo;Lee, Dong-Kun
    • Journal of the Korean Society of Environmental Restoration Technology
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    • v.18 no.2
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    • pp.79-88
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    • 2015
  • Preparations need to be made for Korean pine(Pinus koraiensis) in anticipation of climate change because Korean pine is an endemic species of South Korea and the source of timber and pine nut. Therefore, climate change adaptation policy has been established to conduct an impact assessment on the distribution of Korean pine. Our objective was to predict the distribution of Korean pine while taking into account uncertainty and afforestation conditions. We used the 5th forest types map, a forest site map and BIOCLIM variables. The climate scenarios are RCP 4.5 and RCP 8.5 for uncertainty and the climate models are 5 regional climate models (HadGEM3RA, RegCM4, SNURCM, GRIMs, WRF). The base period for this study is 1971 to 2000. The target periods are the mid-21st century (2021-2050) and the end of the 21st century (2071-2100). This study used the MaxEnt model, and 50% of the presences were randomly set as training data. The remaining 50% were used as test data, and 10 cross-validated replicates were run. The selected variables were the annual mean temperature (Bio1), the precipitation of the wettest month (Bio13) and the precipitation of the driest month (Bio14). The test data's ROC curve of Korean pine was 0.689. The distribution of Korean pine in the mid-21st century decreased from 11.9% to 37.8% on RCP 4.5 and RCP 8.5. The area of Korean pine at an artificial plantation occupied from 32.1% to 45.4% on both RCPs. The areas at the end of the 21st century declined by 53.9% on RCP 4.5 and by 86.0% on RCP 8.5. The area of Korean pine at an artificial plantation occupied 23.8% on RCP 4.5 and 7.2% on RCP 8.5. Private forests showed more of a decrease than national forests for all subsequent periods. Our results may contribute to the establishment of climate change adaptation policies for considering various adaptation options.

Development of climate change uncertainty assessment method for projecting the water resources (기후변화에 따른 수자원 전망의 불확실성 평가기법 개발)

  • Lee, Moon-Hwan;So, Jae-Min;Bae, Deg-Hyo
    • Journal of Korea Water Resources Association
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    • v.49 no.8
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    • pp.657-671
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    • 2016
  • It is expected that water resources will be changed spatially and temporally due to the global climate change. The quantitative assessment of change in water availability and appropriate water resources management measures are needed for corresponding adaptation. However, there are large uncertainties in climate change impact assessment on water resources. For this reason, development of technology to evaluate the uncertainties quantitatively is required. The objectives of this study are to develop the climate change uncertainty assessment method and to apply it. The 5 RCMs (HadGEM3-RA, RegCM4, MM5, WRF, and RSM), 5 statistical post-processing methods (SPP) and 2 hydrological models (HYM) were applied for evaluation. The results of the uncertainty analysis showed that the RCM was the largest sources of uncertainty in Spring, Summer, Autumn (29.3~68.9%), the hydrological model was the largest source of uncertainty in Winter (46.5%). This method can be possible to analyze the changes in the total uncertainty according to the specific RCM, SPP, HYM model. And then it is expected to provide the method to reduce the total uncertainty.