A discussion of some aspects of statistical downscaling in climate impacts assessment
文献类型：EI期刊论文
| 作者 | Liu Chang-Ming |
| 发表日期 | 2012 |
| 关键词 | Statistics Climate change Climate models Uncertainty analysis |
| 英文摘要 | Global Climate Models (GCMs) are the primary tools for understanding how the global climate might change in the future. However, the relatively low spatial resolution of GCMs outputs is unsatisfactory for the local-scale climate impact assessments. Compared to dynamic downscaling, the statistical downscaling approach is widely used to bridge this gap. In this review paper, recent advances in three fundamental statistical downscaling approaches (regression methods, weather type approaches and stochastic weather generators) were presented firstly. Furthermore, uncertainties in statistical downscaling were discussed. The developments and applications of statistical downscaling in China were then summarized. The review study concludes that the comparisons and combinations of statistical downscaling and dynamic downscaling approaches, downscaling of extreme events and uncertainty analysis in statistical downscaling will become the mainstream of future related studies. |
| 出处 | Shuikexue Jinzhan/Advances in Water Science
 |
| 卷 | 23期:3页:427-437 |
| 收录类别 | EI |
| 语种 | 英语 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/27638]  |
| 专题 | 地理科学与资源研究所_历年回溯文献 |
| 推荐引用方式 GB/T 7714 | Liu Chang-Ming. A discussion of some aspects of statistical downscaling in climate impacts assessment. 2012. |
入库方式： OAI收割
来源：地理科学与资源研究所
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