논문 상세보기
pp.225-241
This study investigates the theoretical background of the interpolation methods that regards the topographical effect on the climate data, such as Co-kriging, Artificial Neural Network and MK-PRISM(Modified Korean Parameter-elevation Regressions on Independent Slopes Model). Prior to applying the MK-PRISM to the interpolation of wind speed, this study has improved the model to be closer to the fundamental concept of the PRISM and verified it‘s validity. Since each method has individual advantages and disadvantages, there will be a need for comparative studies in order to select an interpolation method that is suitable for the topography of Korea. This study has added a weighted value that considers the existence of clusters at the known point, and has supplemented the digital elevation models and aspects distribution of multiple scales for application. In addition, this study has allowed the consideration of sharp changes between the known point and unknown point when calculating the topographic facet weighting. The supplement model was verified through the interpolation of rainfall in Jeju Island. The coefficient of determination and KGE(Kling and Gupta Efficiency) of the model displayed the results of 0.86 and 0.87, respectively for August 2010 monthly precipitation in Jeju Island, and the model was accordingly verified. This study is able to provide the necessary information to the researchers who wish to interpolate the observation data of wind speed. Furthermore, the supplement MK-PRISM becomes available to the research on the interpolation of wind speed.
2. 내삽 방법 현황
1) 공동크리깅(Co-kriging)
2) 인공신경망(Artificial Neural Network)
3) MK-PRISM
3. MK-PRISM의 개선
1) 클러스터 가중치의 반영
2) 다중 스케일의 지형고도와 사면방향 분포도
3) 사면방향 가중치 산정방법의 개선
4) 개선 결과의 타당성 검증
5) 풍속 내삽에의 적용 결과
4. 결론
사사
References
