Arid
DOI10.4028/www.scientific.net/AMR.608-609.692
Evaluation of Low-Level Winds from WRF Model that Driven by Different Background Field Data with Applications to Wind Energy Forecasting
Liu, Xiaolin1,2; Yang, Zhaoming2; Jin, Shuanglong1; Wang, Zhiqiang1; Wang, Shigong1
通讯作者Wang, Shigong
会议名称2nd International Conference on Energy, Environment and Sustainable Development (EESD 2012)
会议日期OCT 12-14, 2012
会议地点Jilin, PEOPLES R CHINA
英文摘要

With the large-scale and rapid development of wind power in China, the accuracy of wind power prediction is asked for higher. So how to improve the accuracy of numerical weather prediction models which forecast wind has become an important and critical issue. That the accuracy of numerical prediction models as well as the bias of background data is main cause why generate simulated error. This paper attempted to employ the advanced WRF model to simulate the low-level wind in arid region of northwest China, and then evaluated the impact size that using FNL and GFS background data. The results show that using FNL and GFS data simulated wind is very close. It is found that simulation results driven by the FNL assimilated data are worse sometimes. Consequently, we can conclude that FNL assimilated data as well as GFS forecast data are close and the assimilation of FNL data is still need to improvement in northwest China.


英文关键词WRF model wind simulation background field FNL data GFS data
来源出版物PROGRESS IN RENEWABLE AND SUSTAINABLE ENERGY, PTS 1 AND 2
ISSN1022-6680
出版年2013
卷号608-609
页码692-+
ISBN978-3-03785-549-2
出版者TRANS TECH PUBLICATIONS LTD
类型Proceedings Paper
语种英语
国家Peoples R China
收录类别CPCI-S
WOS记录号WOS:000319300800124
WOS类目Energy & Fuels ; Materials Science, Multidisciplinary
WOS研究方向Energy & Fuels ; Materials Science
资源类型会议论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/301598
作者单位1.Lanzhou Univ, Coll Atmospher Sci, Lanzhou 730000, Gansu, Peoples R China;
2.Meteorol Bur Qinghai Prov, Meteorol Observ Qinghai Prov, Xining 810001, Qinghai, Peoples R China
推荐引用方式
GB/T 7714
Liu, Xiaolin,Yang, Zhaoming,Jin, Shuanglong,et al. Evaluation of Low-Level Winds from WRF Model that Driven by Different Background Field Data with Applications to Wind Energy Forecasting[C]:TRANS TECH PUBLICATIONS LTD,2013:692-+.
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