Applying Satellite Data Assimilation to Wind Simulation of Coastal Wind Farms in Guangdong, China
文献类型：期刊论文
| 作者 | Xu, Wenqing3; Ning, Like1,2; Luo, Yong3 |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2020-03-02 |
| 卷号 | 12期号:6页码:27 |
| 关键词 | data assimilation WRF WRFDA 3DVar |
| DOI | 10.3390/rs12060973 |
| 通讯作者 | Luo, Yong(yongluo@tsinghua.edu.cn) |
| 英文摘要 | With the development of the wind power industry in China, accurate simulation of near-surface wind plays an important role in wind-resource assessment. Numerical weather prediction (NWP) models have been widely used to simulate the near-surface wind speed. By combining the Weather Research and Forecast (WRF) model with the Three-dimensional variation (3DVar) data assimilation system, our work applied satellite data assimilation to the wind resource assessment tasks of coastal wind farms in Guangdong, China. We compared the simulation results with wind speed observation data from seven wind observation towers in the Guangdong coastal area, and the results showed that satellite data assimilation with the WRF model can significantly reduce the root-mean-square error (RMSE) and improve the index of agreement (IA) and correlation coefficient (R). In different months and at different height layers (10, 50, and 70 m), the Root-Mean-Square Error (RMSE) can be reduced by a range of 0-0.8 m/s from 2.5-4 m/s of the original results, the IA can be increased by a range of 0-0.2 from 0.5-0.8 of the original results, and the R can be increased by a range of 0-0.3 from 0.2-0.7 of the original results. The results of the wind speed Weibull distribution show that, after data assimilation was used, the WRF model was able to simulate the distribution of wind speed more accurately. Based on the numerical simulation, our work proposes a combined wind resource evaluation approach of numerical modeling and data assimilation, which will benefit the wind power assessment of wind farms. |
| WOS关键词 | 3DVAR DATA ASSIMILATION ; WEATHER RESEARCH ; SURFACE WIND ; WRF MODEL ; OFFSHORE ; RESOURCE ; SENSITIVITY ; CENTERS |
| 资助项目 | National Key Research and Development Program of China[2018YFB1502803] ; Scientific Research Program of Tsinghua University |
| WOS研究方向 | Remote Sensing |
| 语种 | 英语 |
| WOS记录号 | WOS:000526820600075 |
| 出版者 | MDPI |
| 资助机构 | National Key Research and Development Program of China ; Scientific Research Program of Tsinghua University |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/159654]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Luo, Yong |
| 作者单位 | 1.Chinese Acad Sci, Key Lab Ecosyst Network Observat & Modeling, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 2.Chinese Acad Sci, Yucheng Comprehens Expt Stn, Beijing 100101, Peoples R China 3.Tsinghua Univ, Minist Educ, Key Lab Earth Syst Modeling, Dept Earth Syst Sci, Beijing 100084, Peoples R China |
| 推荐引用方式 GB/T 7714 | Xu, Wenqing,Ning, Like,Luo, Yong. Applying Satellite Data Assimilation to Wind Simulation of Coastal Wind Farms in Guangdong, China[J]. REMOTE SENSING,2020,12(6):27. |
| APA | Xu, Wenqing,Ning, Like,&Luo, Yong.(2020).Applying Satellite Data Assimilation to Wind Simulation of Coastal Wind Farms in Guangdong, China.REMOTE SENSING,12(6),27. |
| MLA | Xu, Wenqing,et al."Applying Satellite Data Assimilation to Wind Simulation of Coastal Wind Farms in Guangdong, China".REMOTE SENSING 12.6(2020):27. |
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。