Journal
SCIENCE OF THE TOTAL ENVIRONMENT
Volume 863, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.scitotenv.2022.160681
Keywords
Multi-objective framework; Dust storm; Dust emission scheme; Dust source function; Center of Iran
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Numerical weather prediction models are crucial for predicting severe weather events like dust storms, but their accuracy depends on various modeling options. In this study, a multi-objective framework is used to determine the optimal options for the WRF-Chem model in simulating a severe dust storm in Iran. The investigation covers 10 options related to grid, physical, and chemical aspects of the model. The results show that the WRF-Chem model has a high capability to simulate dust storms, but the selection of these options significantly affects the forecasting accuracy.
Numerical weather prediction models are very important tools in predicting severe weather phenomena such as dust storms. However, the prediction accuracy in these models depends on the options considered in the modeling. In this study, a multi-objective framework is presented to determine the optimal options of the weather research forecasting with chemistry (WRF-Chem) model. For this purpose, a severe dust storm that occurred in the center of Iran is considered and the effect of 10 options including grid (computational domain size, modeling start time, horizontal, vertical and temporal resolution), physical (initial conditions, boundary layer and land surface schemes) and chemical options (dust emission schemes and dust source functions) are investigated. In general, the results showed that the WRF-Chem model has a high ability to model dust storms, but its results depend on the options considered in the modeling. Evaluation of grid options showed that inappropriate selection of domain size and modeling start time can lead to the failure in dust storm forecasting. Also, the land surface scheme has the greatest impact on dust concentration among the physical options. In addition, chemical options have the greatest impact on the dust storm forecasting as well. Based on the proposed multi-objective framework, the optimal options for dust storm modeling were determined. The proposed approach is comprehensive and can be used for other atmospheric/air quality modeling.
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