Simulation of Wind Speed Based on Different Driving Datasets and Parameterization Schemes Near Dunhuang Wind Farms in Northwest of China
In this study, we evaluate the impacts of different datasets (e.g., NCEP global forecast system (GFS) and ERA5) that are used to derive the initial and boundary conditions, various planetary parameterization boundary layer (PBL) schemes and radiation parameterization schemes on wind speed simulations over wind farms near Dunhuang in Northwest of China. The mesoscale community Weather Research and Forecasting (WRF) model is employed to simulate the wind speeds in March of 2014. The sensitivity
... . The sensitivity of numerical simulations to different PBL schemes, including the Yonsei University (YSU), the Asymmetric Convective Model (ACM2) and the Mellor–Yamada–Janjic (MYJ) scheme are examined. Besides, simulations with different radiation parameterization schemes, including the Rapid Radiative Transfer Model for general circulation model (GCM) applications (RRTMG) and the Fu–Liou–Gu radiative transfer scheme (FLG), are compared. Based on hourly observation data from three national basic meteorological observing stations and an anemometer tower in Dunhuang, the simulation results are evaluated. Results show that, using the GFS data as the initial data, the simulation error of 10-m wind speed is rather smaller under the combination of the YSU and FLG. When using the ERA5 data as the initial data, the error of the 2-m temperature simulation is smaller, and it is also less than that of the 10-m wind speed simulation. The simulation results show significant differences at different altitudes. The relative error of wind speed is larger at higher altitude. In the vertical direction, the wind speed is smaller at a lower height and so is the simulation error. In terms of wind speed from the anemometer tower, the error of the wind speed is related to the magnitude of the observed wind speed. Therefore, according to specific conditions of the simulated area, selecting an appropriate combination of initial data and parameterization schemes can effectively reduce the errors of simulated wind speed.