기온감율을 적용한 기후자료가 잠재 산림분포 예측에 미치는 영향

국문 초록 (Abstract)

본 연구의 목적은 기후변화에 따른 잠재 산림분포 예측에 이용되는 기상 자료의 효과적인 구축 및 규모변환(Down Scaling) 방법을 제시 하는 것이다. 잠재 산림분포 예측을 위해 한국형 산림 분포 모형 TAC(Thermal Analogy Group)의 예측 방법과 HyTAG(Hydrological and Thermal Analogy Croup)에서 정의한 식생 기능성 유형(PFT: Plant Functional Types)을 함께 적용하였다. 이를 위해 20㎞ 공간해상도의 기상자료를 1㎞의 공간해상도에 부합하도록 보간 하였다. 이러한 보간 및 규모변환의 한 가지 방법으로 고도에 따른 기온감율을 적용 및 비적용하여 각각의 과거 잠재 산림분포를 예측하였다. 현존 산림분포도와 비교한 정확도 검증에서 기온감율을 적용한 잠재 산림분포가 약 38% 더 정확한 것으로 나타났다.

다국어 초록 (Multilingual Abstract)

The objective of this study was to suggest technical approaches for preparation and down scaling of climate data used for predicting the potential forest distribution. To predict the forest distribution, we employed a Korean-specific forest distribution model, so-called the TAG(Thermal Analogy Group), and defined the PFT(Plant Functional Types) based on the HyTAG(Hydrological and Thermal Analogy Group). The climate data with 20㎞ spatial resolution were interpolated to fit on the input data format with 1㎞ spatial resolution. Two potential forest distribution maps were estimated using climate data constructed by kriging, one of the interpolation and down-scaling approaches, with and without lapse rate considered. Through the verification process by comparing two potential maps with the actual vegetation map, the forest distribution using the lapse rate was proven to be 38% more accurate.

목차 (Table of Contents)

• 要旨
• Abstract
• 1. 서론
• 2. 재료 및 방법
• 3. 결과 및 고찰
• 4. 결론
• 감사의 글
• 참고문헌

참고문헌 (Reference)

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