Evaluation of Low-Level Winds from WRF Model that Driven by Different Background Field Data with Applications to Wind Energy Forecasting

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.