The process of synthesis and determination which are analyzing climate and making agro-climatic index of agricultural areas makes it possible to easily understand the characteristics of agricultural climate resources in the agricultural region. agro-climatic index is to assess the climate resources of particular agricultural areas on ‘the view of agricultural production’; it can be a key indicator of agricultural productivity by providing the basic information required for the implementation of different and various farming techniques and probabilities to estimate the growth and yield of crops from the climate resources such as air temperature, solar radiation, and precipitation. however, the distribution of agricultural climate resources vary depending on the climate change and the index can always be changed because it is not an absolute. Rcp(representative concentration pathways) future scenarios of the Fifth assessment Report of Ipcc(intergovernmental panel on climate change) have been used in many recent studies. By developing and improving dynamic downscaling of climate information as well as statistical downscaling, many studies which are considering on the uncertainty of future climate change have been being actively conducted with multiple ensemble approach.

In this study, agro-climatic index of Korean peninsula, for example, plant and crop period based on each base temperature, growing degree day, frost free day, and heating and cooling degree day were calculated for assessment its temporal and spatial variations and uncertainties on climate change; the downscaled historical climate(1976-2005) and Rcp future climate scenarios of aR5(2011-2040) were applied to the calculation of the index. In addition, we considered on the practicability of the agro-climatic indices in the study with agricultural digital climate map of RDa(rural development administration). It was compared with that between the agro-climatic index calculated by the historical climate and the agro-climatic index calculated by the observed data. the result showed each average of six agro-climatic indices of nine individual global climate models, as well as multiple ensembles agreed with agro-climatic indices calculated by the observed data, and it was confirmed that multiple ensembles, as well as each individual global climate model can emulate well on past climate in the four Rivers(han, Nakdong, Geum, and Yeoungsan and seumjin). the six agro-climatic indices of Korean peninsula were estimated to be increased at nine individual global climate models and multiple ensembles in future scenarios. however, the improvement of spatial downscaling methods still needs since the agro-climatic indices of some individual global climate models showed different variations with the observed indices in the change of spatial distribution in four Rivers.

Additionally, the differences and uncertainties of between agro-climatic indices calculated by the observed and global climate models haven’t been reduced on unlimited coupling of multiple ensembles. Further research is still required, however, the differences were started improving at the combining of three or four individual global climate models, and the differences didn’t improve anymore at the coupling of mostly seven or eight individual global climate models in the study. agro-climatic indices derived and evaluated in the study will be the baseline for the assessment of agro-climatic abnormal indices and agro-productivity indices of the next research work. For example, if we can assume that the winter temperature will be decreased in the regions since the heating degree day has been estimated to be increased in Nakdong River, and Yeoungsan and seumJin River in the future climate, the assessment of the heating degree day of the regions will be able to take advantage of assessment of the increasing of the uncertainty of agro- productivity of winter crop or the increasing of the uncertainty of agricultural system(e.g., double cropping system) by analyzing agro-climatic abnormal index(e.g., frequency of frost).

1. 서론

2. 연구자료 및 방법

2.1 상세화된 기후예측정보

2.1.1 CMIP5 자료

2.1.2 편의보정 및 상세화

2.2 농업기후지수

2.2.1 농업기후지수 정의와 종류

2.3 분석방법

2.3.1 비교기간 및 공간규모

2.3.2 통계적 분석방법

2.3.3 공간내삽

3. 연구결과

3.1 농업기후지수의 변화

3.1.1 식물기간과 작물기간

3.1.2 생장도일의 변화

3.1.3 무상일수의 변화

3.1.4 난방도일과 냉방도일의 변화

3.2 농업기후지수의 공간분포 변화와 불확실성 전망

3.2.1 기후모델의 재현성

3.2.2 공간변화와 불확실성

3.2.3 농업기후지수의 미래전망과 불확실성

3.3 다중모델앙상블 효율성

3.3.1 Multimodel ensemble estimators

4. 결론 및 고찰

4.1 농업기후지수의 변화

4.2 농업기후지수의 재현성과 미래전망의 불확실성

4.3 다중모델앙상블 효율성 평가

5. 활용성 및 정책시사

5.1 지역-맞춤형 적응정책

5.2 기초정보

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