Effects of the Subgrid-Scale Orography Parameterization and High-Resolution Surface Data on the Simulated Wind Fields in the WRF Model under the Different Synoptic-Scale Environment

This study evaluates the simulated meteorological fields with a particular focus on the low-level wind, which plays an important role in air pollutants dispersion, under the varying synoptic environment. Additionally, the effects of subgrid-scale orography parameterization and improved topography/land-use data on the simulated low-level wind is investigated. The WRF model version 4.1.3 is utilized to simulate two cases that were affected by different synoptic environments. One case from 2 to 6 April 2012 presents the substantial low-level wind speed over the Korean peninsula where the synoptic environment is characterized by the baroclinic instability. The other case from 14 to 18 April 2012 presents the relatively weak low-level wind speed and distinct diurnal cycle of low-level meteorological fields. The control simulations of both cases represent the systematic overestimation of the low-level wind speed. The positive bias for the case under the baroclinic instability is considerably alleviated by applying the subgrid-scale orography parameterization. However, the improvement of wind speed for the other case showing relatively weak low-level wind speed is not significant. Applying the high-resolution topography and land-use data also improves the simulated wind speed by reducing the positive bias. Our analysis shows that the increased roughness length in the high-resolution topography and land-use data is the key contributor that reduces the simulated wind speed. The simulated wind direction is also improved with the high-resolution data for both cases. Overall, our study indicates that wind forecasts can be improved through the application of the subgridscale orography parameterization and high-resolution topography/land-use data.