Wind field simulation using WRF model in complex terrain: A sensitivity study with orthogonal design

Accurately simulating wind speed is of utmost importance for wind power assessments. The objective of this study is to investigate the performance of wind speed simulation in complex terrain using different parameterization schemes from the Weather Research and Forecasting (WRF) model, employing an orthogonal design methodology. Specifically, nine WRF simulations are conducted based on the orthogonal test, considering various configurations of the planetary boundary layer (PBL), microphysics (MP), and land surface (LS) options. The numerical results are then compared to actual wind data obtained from a measuring station at two different heights (50 m and 80 m) during summer and winter periods. Furthermore, range and variance analyses are employed to rank the three schemes and identify the optimal combination. Moreover, we examine the impact of each parameterization scheme on the accuracy of wind speed predictions based on the results obtained from the orthogonal simulations. Additionally, we discuss the influence of using different evaluation indices within the orthogonal test on the outcomes and analyze the WRF simulated results under the optimal scheme combination. Lastly, we conduct an uncertainty analysis of results from the optimal scheme combination. The findings reveal that both the PBL and MP schemes exhibit highly significant effects on the accuracy of wind speed predictions (significance: **), followed by the LS scheme (significance: *). The order of importance for these three options is ranked as follows: PBL > MP > LS, which is independent of the seasons. The optimal configurations vary from summer and winter periods. Specifically, the optimal scheme combination is determined to be PBL-ACM2, MPKessler, and LS-Noah MP in summer, while PBL-BouLac, MP-Lin, and LS-Noah MP in winter. The simulating accuracy of the wind speeds is satisfactory under this optimal combination when considering the uncertainty of on-site measurements during these two periods. These results provide valuable insights for selecting appropriate PBL, MP, and LS options (from the WRF model) for wind speed estimates and wind power development in the studied region.