A Comparative Study on GCM Multi-Model Ensemble Techniques for Water Resources Management

• 발행기관: 한국방재학회
• 저자명: 오랑치맥 솜야(Uranchimeg, Sumiya) 권현한(Kwon Hyun Han) 윤선권(Yoon Sun Kwon)
• 간행물 정보: 『3. 한국방재학회 학술대회논문집』2015년, 249~249쪽, 전체 1쪽
• 주제분류: 공학 > 기타공학
• 파일형태: PDF
• 발행일자: 2015.02.25

영문 초록

Seasonal rainfall forecasts are one of the most important part of water resources management in minimizing climate-related risk. Recently, abnormal change in precipitation raised the attention of not only scientists it gets big interest in general public too. Seasonal climate forecasts are typically based on simulations from general circulation models (GCMs) that approximate the complex physical, chemical, and biological processes. But it has been known that General Circulation Models have considerable uncertainties. Recent studies suggested that Multi-Model Ensemble(MME) could reduce this uncertainties and give an improvement on the results. There have been used several MME estimation techniques that are simply averaging models and regression based techniques. This study aims to improve MME using Bayesian Model Averaging(BMA) technique which gives weights to the models based on each model performance to present observation. The result showed that BMA technique output is statistically more fitted to the observation than the other techniques and it is very important to further analysis such as downscaling and other simulation method that uses future precipitation as a main input data.

키워드

Multi-Model Ensemble General Circulation Model Bayesian Model Averaging