Using the Back Propagation Neural Network Approach to Bias Correct TMPA Data in the Arid Region of Northwest China
文献类型：SCI/SSCI论文
| 作者 | Luo Y. |
| 发表日期 | 2014 |
| 关键词 | Remote sensing Precipitation satellite rainfall products precipitation analysis tmpa passive microwave gauge observations tibetan plateau complex terrain cost estimation united-states trmm validation |
| 英文摘要 | Scarcity or unavailability of precipitation observation creates difficulties in hydrologic modeling of mountainous sections of the arid region of northwest China (34 degrees-50 degrees N, 72 degrees-107 degrees E). Tropical Rainfall Measuring Mission (TRMM) precipitation products may be a potential substitute, but they should be evaluated and corrected with ground observation data before application. In this paper, two TRMM Multisatellite Precipitation Analysis (TMPA) precipitation products were evaluated by gauge observations, using indices such as frequency bias index, probability of detection, false alarm ratio, relative mean bias, Nash-Sutcliffe efficiency, and correlation coefficient. Terrain variables were extracted from a digital elevation model, and their rotated principal components were determined to establish a stepwise regression model to adjust TMPA precipitation. Additionally, a back-propagation (BP) neural network was established to correct TMPA precipitation. The results showed that TMPA had an unsatisfactory detection ability in the study area for both precipitation occurrence and amount. TMPA precipitation corrected by a stepwise regression method showed some improvement, but only the results for TRMM 3B43 on a subregion scale were acceptable. The BP neural network method showed better results than the stepwise regression method, and both TRMM 3B42 and TRMM 3B43 corrected by the former method on a subregion scale could be acceptable. Both methods were spatial-scale dependent and showed better results on a subregion scale than on a larger scale. |
| 出处 | Journal of Hydrometeorology |
| 卷 | 15 |
| 期 | 1 |
| 页 | 459-473 |
| 收录类别 | SCI |
| 语种 | 英语 |
| ISSN号 | 1525-755X |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/29455]  |
| 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 | Luo Y.. Using the Back Propagation Neural Network Approach to Bias Correct TMPA Data in the Arid Region of Northwest China. 2014. |
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。