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NTIS 바로가기한국농공학회논문집 = Journal of the Korean Society of Agricultural Engineers, v.57 no.2, 2015년, pp.1 - 13
남원호 (National Drought Mitigation Center, School of Natural Resources, University of Nebraska-Lincoln) , 홍은미 (USDA-ARS Environmental Microbial & Food Safety Laboratory, Beltsville Agricultural Research Center) , 최진용 (Department of Rural Systems Engineering and Research Institute for Agriculture & Life Sciences, Seoul National University) , 조재필 (Climate Research Department, APEC Climate Center)
The Coupled Model Intercomparison Project Phase 5 (CMIP5), coordinated by the World Climate Research Programme in support of the Intergovernmental Panel on Climate Change (IPCC) AR5, is the most recent, provides projections of future climate change using various global climate models under four majo...
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핵심어 | 질문 | 논문에서 추출한 답변 |
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기후변화 영향평가 과정의 단계별 불확실성 주요 원인은 무엇인가? | , 2013). 또한 기후변화 영향평가 과정에서 발생되는 불확실성 중 주요 원인은 기후변화 시나리오 선택에 의한 불확실성으로 제시된 바있다 (Harding et al., 2012; Lee and Kim, 2012; Madsen et al. | |
IPCC의 제 5차 기후변화 평가보고서는 무엇을 기반으로 작성되었나? | 기후변화에 관한 정부간 협의체 (Intergovernmental Panel on Climate Change, IPCC)의 제 5 차 기후변화 평가보고서(the Fifth Assessment Report, AR5)는 2007년에서 2011년까지 실시된 5 단계 결합모델 상호비교 프로젝트 (the phase five of the Coupled Model Intercomparison Project, CMIP5)를 통해 신 온실가스 배출 시나리오를 기반으로 작성되었다. 전 지구 기후변화 시나리오 산출을 위한 국제사업인 CMIP5 사업은 전 세계 23개 기후 연구 그룹이 참여하고 50 개 이상의 기후모델을 이용하여 온실가스의 대표농도경로 (Representative Concentration Pathways, RCP) 시나리오 기반의 기후전망자료를 제공하고 있다 (Cho, 2013; Hwang, 2014a). | |
기후변화 불확실성에 대한 선행 연구는 어떤 요소들을 중심으로 진행되었는가? | 기후변화 불확실성에 대한 선행 연구는 미래 온실 가스 배출 시나리오 예측의 부정확성, 저해상도 기후모델 결과의 시공간적인 편의를 보정하는 방법에 따른 오차, 적용 모형의 선정과 매개변수 보정에 따른 오차 등 기후변화 영향평가 과정의 단계별 불확실성 요소에 관한 연구가 진행되었다 (Raje and Mujumdar, 2010; Bae et al., 2011; Hwang and Kang, 2013; No et al. |
Cho, J.P., 2013. Impact assessment of climate change for agricultural reservoirs considering uncertainty. Research Report, APEC climate Center, Busan, Republic of Korea (in Korean).
Chung, S.O., and T. Nkomozepi, 2012. Uncertainty of paddy irrigation requirement estimated from climate change projections in the Geumho river basin, Korea. Paddy Water Environment 10: 175-185.
Collins, M., B.B.B. Booth, G.R. Harris, J.M. Murphy, D.M.H. Sexton, and M.J. Webb, 2006. Towards quantifying uncertainty in transient climate change. Climate Dynamics 27: 127-147.
Collins, M., R.E. Chandler, P.M. Cox, J.M. Huthnance, J. Rougier, and D.B. Stephenson, 2012. Quantifying future climate change. Nature Climate Change 25: 403-409.
Elguindi, N., A. Grundstein, S. Bernardes, U. Turuncoglu, and J. Feddema, 2014. Assessment of CMIP5 global model simulations and climate change projections for the 21st century using a modified Thornthwaite climate classification. Climatic Change 122: 523-538.
Feddema, J.J., 2005. A revised thornthwaite-type global climate classification. Physical Geography 26(6): 442-466.
Garcia-Garizabal, I., J. Causape, R. Abrahao, and D. Merchan, 2014. Impact of climate change on mediterranean irrigation demand: historical dynamics of climate and future projections. Water Resources Management 28: 1449-1462.
Gober, P., C.W. Kirkwood, R.C. Balling Jr., A.W. Ellis, and S. Deitrick, 2010. Water planning under climatic uncertainty in Phoenix: why we need a new paradigm. Annals of the Association of American Geographers 100(2): 356-372.
Greve, P., B. Orlowsky, B. Mueller, J. Sheffield, M. Reichstein, and S.I. Seneviratne, 2014. Global assessment of trends in wetting and drying over land. Nature Geoscience 7: 716-721.
Harding, B.L., A.W. Wood, and J.R. Prairie, 2012. The implications of climate change scenario selection for future streamflow projection in the upper Colorado river basin. Hydrology and Earth System Sciences 16: 3989-4007.
Hong, E.M., J.Y. Choi, S.H. Lee, S.H. Yoo, and M.S. Kang, 2009. Estimation of paddy rice evapotranspiration considering climate change using LARS-WG. Journal of the Korean Society of Agricultural Engineers 51(3): 25-35 (in Korean).
Hwang, S.W., and M.S. Kang, 2013. Uncertainty of climate change impact assessment methodology and process. Magazine of the Korean Society of Agricultural Engineers 55(1): 30-39 (in Korean).
Hwang, S.W., 2014a. Summary and comparison of the climate change predictions of IPCC climate change scenarios and assessment report. Magazine of the Korean Society of Agricultural Engineers 56(2): 26-32 (in Korean).
Lee, J.K., and Y.O. Kim, 2010. A study on selection of standard scenarios in Korea for climate change. Climate Change Research 1(1): 59-73 (in Korean).
Lee, J.K., and Y.O. Kim, 2012. Selecting climate change scenarios reflecting uncertainties. Atmosphere. Korean Meteorological Society 22(2): 149-161 (in Korean).
Madsen, M.S., C.F. Maule, N. MacKellar, J.E. Olesen, and J.H. Christensen, 2012. Selection of climate change scenario data for impact modelling. Food Additives & Contaminants: Part A 29(10): 1502-1513.
Moon, H.J., B.H. Kim, H.E. Oh, J.Y. Lee, and K.J. Ha, 2014. Future change using the CMIP5 MME and best models: I. near and long term future change of temperature and precipitation over East Aisa. Atmosphere. Korean Meteorological Society 24(3): 403-417 (in Korean).
Murdock, T.Q., and D.L. Spittlehouse, 2011. Selecting and using climate change scenarios for British Columbia. Pacific Climate Impacts Consortium, University of Victoria, Victoria, BC.
Nam, W.H., E.M. Hong, and J.Y. Choi, 2014a. Uncertainty of water supply in agricultural reservoirs considering the climate change. Journal of the Korean Society of Agricultural Engineers 56(2): 11-23 (in Korean).
Nam, W.H., E.M. Hong, T.G. Kim, and J.Y. Choi, 2014b. Projection of future water supply sustainability in agricultural reservoirs under RCP climate change scenarios. Journal of the Korean Society of Agricultural Engineers 56(4): 59-68 (in Korean).
Nam, W.H., E.M. Hong, M.W. Jang, and J.Y. Choi, 2014c. Projection of consumptive use and irrigation water for major upland crops using soil moisture model under climate change. Journal of the Korean Society of Agricultural Engineers 56(5):77-87 (in Korean).
Nam, W.H., E.M. Hong, and J.Y. Choi, 2015. Has climate change already affected the spatial distribution and temporal trends of reference evaptranspiration in South Korea?. Agricultural Water Management 150: 129-138.
Oh, S.G., and M.S. Suh, 2013. Projection of fine-scale climate changes over South Korea based on the RCP (2.6, 4.5, 6.0, 8.5) scenarios using RegCM4. Journal of Climate Research 8(4):291-307 (in Korean).
Raje, D., and P.P. Mujumdar, 2010. Reservoir performance under uncertainty in hydrologic impacts of climate change. Advances in Water Resources 33: 312-326.
Rowland, E.R., M.S. Cross, and H. Hartmann, 2014. Considering multiple futures: scenario planning to address uncertainty in natural resource conservation. Washington, DC, US Fish and Wildlife Service.
Snover, A.K., N.J. Mantua, J.S. Littell, M.A. Alexander, M.M. Mcclure, and J. Nye, 2013. Choosing and using climate-change scenarios for ecological-impact assessments and conservation decisions. Conservation Biology 27: 1147-1157.
Sung, J.H., H.S. Kang, S.H. Park, C.H. Cho, D.H. Bae, and Y.O. Kim, 2012. Projection of extreme precipitation at the end of 21st century over South Korea based Representative Concentration Pathways (RCP). Atmosphere. Korean Meteorological Society 22(2): 221-231 (in Korean).
Thornthwaite, C.W., 1948. Approach toward a rational classification of climate. Geographical Review 38: 55-94.
Willmott, C.J., and J.J. Feddema. 1992. A more rational climatic moisture index. The Professional Geographer 44(1):84-88.
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