Development of a statistical downscaling approach for projecting future river runoff from GCM outputs

被引：0
|
作者：
Liu, C. M. [1 ]
Lin, S. H. [1 ]
Lin, S. S. [1 ]
Yen, T. H. [1 ]
Kuo, J. T. [1 ]
机构：
[1] Natl Taiwan Univ, Global Change Res Ctr, Taipei, Taiwan
来源：
PROCEEDINGS OF THE SECOND IASTED INTERNATIONAL CONFERENCE ON WATER RESOURCES MANAGEMENT | 2007年
关键词：
statistical downscaling; GCM; river runoff; climate change;
D O I：
暂无
中图分类号：
X [环境科学、安全科学];
学科分类号：
08 ; 0830 ;
摘要：
In this study, a statistical approach is adopted to project the temperature and precipitation field of the 21(st) century under SIZES A2, B2 over Taiwan (similar to 150 x 400 km(2)) based on the global circulation model (GCM) outputs.. Multivariate regression is used to build the relationship between GCM outputs and local observed climate data, and, thereafter, to project the future climate. In the meantime, artificial neural network has been applied to estimate the river runoff based on the projected climatic parameters. Results of projected change of river runoff are then evaluated.
引用
收藏
页码：220 / +
页数：3
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