A comparison of two downscaling methods for precipitation in China
文献类型：SCI/SSCI论文
| 作者 | Zhao N.; Chen, C. F.; Zhou, X.; Yue, T. X. |
| 发表日期 | 2015 |
| 关键词 | Global climate models Statistical downscaling method GWR HASM Precipitation China geographically weighted regression climate-change water-resources united-kingdom rainfall basin products model trmm impacts |
| 英文摘要 | In most cases, climate change projections from General Circulation Models (GCM) and Regional Climate Models cannot be directly applied to climate change impact studies, and downscaling is, therefore, needed. A large number of statistical downscaling methods exist, but no clear recommendations exist of which methods are more appropriate, depending on the application. This paper compares two different statistical downscaling methods, Pre(sim1) and Pre(sim2), using the Coupled Model Intercomparison Project Phase 5 (CMIP5) datasets and station observations. Both methods include two steps, but the major difference between them is how the CMIP5 dataset and the station data used. The downscaled precipitation data are validated with observations through China and Jiangxi province from 1976 to 2005. Results show that GCMs cannot be used directly in climate change impact studies. In China, the second method Pre(sim2), which establishes regression model based on the station data, has a tendency to overestimate or underestimate the real values. The accuracy of Pre(sim1) is much better than Pre(sim2) based on mean absolute error, mean relative error and root mean square error. Pre(sim1) fuses the mode data and station data effectively. Results also show the importance of the meteorological station data in the process of residual modification. |
| 出处 | Environmental Earth Sciences |
| 卷 | 74 |
| 期 | 8 |
| 页 | 6563-6569 |
| 收录类别 | SCI |
| 语种 | 英语 |
| ISSN号 | 1866-6280 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/39066]  |
| 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 | Zhao N.,Chen, C. F.,Zhou, X.,et al. A comparison of two downscaling methods for precipitation in China. 2015. |
入库方式： OAI收割
来源：地理科学与资源研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。