Downscaling GCMs Using the Smooth Support Vector Machine Method to Predict Daily Precipitation in the Hanjiang Basin |
| |
| Authors: | CHEN Hu GUO Jing XIONG Wei GUO Shenglian and Chong-Yu XU |
| |
| Institution: | State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072,State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072,Radar and Avionics Institute of Aviation Industry Corporation of China, Wuxi 214063,State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072,Department of Geosciences, University of Oslo, PO Box 1047 Blindern, NO-0316 Oslo, Norway |
| |
| Abstract: | General circulation models (GCMs) are often used in assessing the impact of climate change at global and continental scales. However, the climatic factors simulated by GCMs are inconsistent at comparatively smaller scales, such as individual river basins. In this study, a statistical downscaling approach based on the Smooth Support Vector Machine (SSVM) method was constructed to predict daily precipitation of the changed climate in the Hanjiang Basin. NCEP/NCAR reanalysis data were used to establish the sta... |
| |
| Keywords: | SSVM GCM statistical downscaling precipitation Hanjiang Basin |
| 本文献已被 CNKI 维普 万方数据 SpringerLink 等数据库收录！ |
| 点击此处可从《大气科学进展》浏览原始摘要信息 |
| 点击此处可从《大气科学进展》下载免费的PDF全文 |
|
