AOD adaptive prediction method based on GNSS PWV

Aerosol optical depth (AOD) is a basic parameter of total aerosol content, which plays an important role in the study of atmospheric air quality. In order to explore the impact of different types of AOD on air quality, this paper proposes two adaptive AOD prediction methods based on GNSS PWV. The proposed method considers the temporal autocorrelation of AOD between adjacent epochs, and the model coefficients can be updated adaptively. One method is to model the 550 nm AOD directly based on GNSS PWV, which is called TAF (total AOD forecast) model. Another AOD modeling method takes into account the sensitivity of five different types of AOD to PWV, referred to it simply as FTAF(five type based AOD forecast) model. The model first establishes the functional relationship between PWV and five types of AOD. Secondly, according to the relationship between 550 nm AOD and five types of AOD, the weight of different types of AOD in 550 nm AOD was determined. Finally, PWV is used to predict five types of AOD, and the final 550 nm AOD is obtained by weighted average. 16 GNSS stations in Beijing, Tianjin, Hebei region are selected to verify the accuracy of the proposed model. The results show that the two 550 nm AOD prediction models have high accuracy, and the FTAF model is better than the TAF model. The AOD prediction model proposed in this paper can effectively apply the tropospheric parameters retrieved from GNSS to remote sensing monitoring of atmospheric environment, which provides a new idea for the study of atmospheric environmental quality.