Abstract
To make a reliable forecast for the level of dust, many external factors such as the wind energy and the soil content in the moisture must be considered. The numerical prediction of the Black sea region’s content of dust is the focus of this study, and for this purpose, the WRF-Chem model is used. The investigation is based on the statistics of the prediction coincidence and the actual result extracted from the data of the backward trajectories of AERONET and aerosol stratification maps in the atmosphere constructed with the help of the CALIPSO satellite. A comprehensive set of data was collected, and a comparative analysis of the results was carried out using machine learning techniques. The investigation identified 89% hits in the prediction of dust events, which is a very satisfactory result.
Highlights
This paper evaluates the numerical prediction of dust content using the WRF-Chem, for the Black Sea region based on the statistics of the prediction coincidence and the actual result
The territorial feature of the Black Sea region is such that the frequent dustiness of the atmosphere in the region is clearly apparent, which established the need for the investigation
The end level collaboration, as mentioned, is in the 1.5 level and for the AERONET the returning of the trajectories is considered for the optical thickness estimation of the aerosols, which confirmed the presence of 33 dust transfers towards the
Summary
The Weather Research and Forecasting Model is abbreviated as the WRF-Chem model as it has mixed chemistry. The focus of this model is to study the transfer or emission of gaseous impurities and chemical conversions inside the aerosols and how they are linked with the meteorology. This model can be effectively used to study air quality on a regional scale. It can be used as a supplement when identifying the place of origin of dust aerosol, which is very useful in studying the physicochemical properties of aerosol [5]
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