عنوان مقاله [English]
The wind is one of the main factors in determining the weather condition and the daily air quality of urban spaces depends on the wind. Therefore, to achieve the dominant behavioral patterns of wind direction and intensity, various simulation models are used. In this study, the weather research and forecasting model (WRF) is considered. To simulate wind zonal and meridional components, the role of ECMWF (ERA5) and NCEP (FNL) boundary condition data with 7 physical schemas (Exp1 to Exp7) in two modes: 1) with default static data and, 2) with high-resolution static data DEM (Aster satellite image with a spatial resolution of 30 m) instead of the default data with a spatial resolution of approximately 1 km, the land use/cover of Copernicus with a resolution of 100 m instead of the modis data with a spatial resolution of approximately 500 m to 1 km) for January, May, July, and October 2018 was evaluated as representative of seasons. Observational data of wind direction and speed with a 3-hour UTC scale in 2018 for 4 synoptic stations of Mehrabad, Chitgar, Geophysics, and Shemiran were obtained from the Meteorological Organization and by applying 180 degrees to the weather direction, the vector orientation was obtained. Then, using the Rewind plugin in the developed R software, the zonal and meridian components of observational wind were calculated. By examining the correlation coefficient of wind zonal component in 4 selected stations in both default and high-resolution conditions with ERA5 and FNL boundary conditions, Shemiran station had the lowest correlation in January, May, and October, while Chitgar station on the suburban of the city had the weakest correlation in July; However, Shemiran station had the strongest correlation in July by a significant margin. Due to the location of the Shemiran station, the main reason for the weakness and strength of the simulations is the topography and height of this station. The results show that the simulation of the wind zonal component, except July in most schemas with the default static data and high resolution, is much better than the meridional component. Proper configuration of schemas, selection of ideal boundary conditions, determination of appropriate spatial resolution, and replacement of static data with a high resolution instead of default data can bring the model simulation much closer to the observation data. According to the results of the average output of 4 correlations, bias, mean square error, and mean absolute error statistics, considering the same weight coefficient of each statistic in Mehrabad, Geophysics, Shemiran, and Chitgar stations for each schema, FNL boundary conditions with default static data for the component Wind except July, and ERA5 boundary conditions were selected as the best boundary conditions for the meridional wind component except January with the best performance. Among the seven schemas tested for zonal and meridional components under the ERA5 and FNL boundary conditions with default and high-resolution data, Exp (1) (YSU) and Exp (6) (ACM2) generally yielded the best results for Tehran wind simulation.