통계적 축소법을 이용한 한반도 인근해역의 미래 표층수온 추정

• 영문명: Prediction of Future Sea Surface Temperature around the Korean Peninsular based on Statistical Downscaling
• 발행기관: 강원대학교 산업기술연구소
• 저자명: 함희정(Ham, Hee-Jung) 김상수(Kim, Sang-Su) 윤우석(Yoon, Woo-Seok)
• 간행물 정보: 『산업기술연구』vol.31, 107~112쪽, 전체 6쪽
• 주제분류: 공학 > 공학일반
• 파일형태: PDF
• 발행일자: 2011.09.30

영문 초록

Recently, climate change around the world due to global warming has became an important issue and damages by climate change have a bad effect on human life. Changes of Sea Surface Temperature(SST) is associated with natural disaster such as Typhoon and El Nino. So we predicted daily future SST using Statistical Downscaling Method and CGCM 3.1 A1B scenario. 9 points of around Korea peninsular were selected to predict future SST and built up a regression model using Multiple Linear Regression. CGCM 3.1 was simulated with regression model, and that comparing Probability Density Function, Box-Plot, and statistical data to evaluate suitability of regression models, it was validated that regression models were built up properly.

목차

1. 서론

2. 사용자료

3. 축소법

4. 결과

5. 결론

키워드

표층수온 통계적축소법 선형회귀분석 Sea Surface Temperature Statistical Downscaling Linear Regression