Journal of The Korean Society of Agricultural Engineers (한국농공학회논문집)

The Korean Society of Agricultural Engineers (한국농공학회)
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Uncertainty Characteristics in Future Prediction of Agrometeorological Indicators using a Climatic Water Budget Approach

기후학적 물수지를 적용한 기후변화에 따른 농업기상지표 변동예측의 불확실성

  • Nam, Won-Ho (National Drought Mitigation Center, School of Natural Resources, University of Nebraska-Lincoln) ;
  • Hong, Eun-Mi (USDA-ARS Environmental Microbial & Food Safety Laboratory, Beltsville Agricultural Research Center) ;
  • Choi, Jin-Yong (Department of Rural Systems Engineering and Research Institute for Agriculture & Life Sciences, Seoul National University) ;
  • Cho, Jaepil (Climate Research Department, APEC Climate Center) ;
  • Hayes, Michael J. (National Drought Mitigation Center and School of Natural Resources, University of Nebraska-Lincoln)
  • Received : 2014.12.18
  • Accepted : 2015.01.21
  • Published : 2015.03.31
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Abstract

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 major greenhouse gas emission scenarios. There is a wide selection of climate models available to provide projections of future climate change. These provide for a wide range of possible outcomes when trying to inform managers about possible climate changes. Hence, future agrometeorological indicators estimation will be much impacted by which global climate model and climate change scenarios are used. Decision makers are increasingly expected to use climate information, but the uncertainties associated with global climate models pose substantial hurdles for agricultural resources planning. Although it is the most reasonable that quantifying of the future uncertainty using climate change scenarios, preliminary analysis using reasonable factors for selecting a subset for decision making are needed. In order to narrow the projections to a handful of models that could be used in a climate change impact study, we could provide effective information for selecting climate model and scenarios for climate change impact assessment using maximum/minimum temperature, precipitation, reference evapotranspiration, and moisture index of nine Representative Concentration Pathways (RCP) scenarios.

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References

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