资源环境科技发展态势分析平台

Dust significantly influences the radiation budget by absorbing and scattering solar radiation, changing the heating/cooling rates, and reducing radiation incoming to change the atmospheric thermal and dynamics conditions, this subsequently affects the accuracy of weather forecasting itself. However, the currently operational numerical models for weather prediction systems rarely consider dust aerosol's impact. Two sets of experiments based on the Weather Research and Forecasting model coupled with chemistry (WRF-Chem) were conducted in this study to simulate a heavy dust storm (6–9 June 2020) over Taklimakan Desert while considering the radiative effects of dust (called DUST) and ignoring them (NoDUST). The simulations were associated with in-situ measurements and MODIS aerosol optical to evaluate the dust effect. The results show that the overestimation of SW radiation reduced significantly in DUST compared with NoDUST, dust-induced radiative forcing had a net warming effect on the atmosphere (47.8 W/m²) and a cooling effect on the surface (−62.6 W/m²). The surface radiation budget also improved in DUST, which accompanied the considerable reduction in SW radiation in the sensible heat flux to 57 W/m², which was better agree with measurements. The interactions of dust radiation significantly adjusted the stability of the boundary layer and lowered its height. Further, the verification indicated that the warm biases in the 2 m temperature and the overestimation of wind speed reduced by 20.6% and 6.6%, respectively. The atmospheric temperature and wind speed in vertical dimension layers were verified by radio-sounding, indicating that the dust radiation effect helped to alleviate forecasting bias. Thus, the effect of dust radiation should be considered in the operational weather forecasting system to improve forecasting accuracy, particularly in arid and semi-arid areas dust-affected.