A Spatio-Temporal Weighted Filling Method for Missing AOD Values

• Published in: Atmosphere
• Main Authors: Rongfeng Gao, Xiaoping Rui, Jiakui Tang
• Format: Article in Journal/Newspaper
• Language: English
• Published: MDPI AG 2022
• Subjects: Beijing–Tianjin–Hebei; MAIAC AOD; spatio-temporal weighted; AOD fill; Meteorology. Climatology; QC851-999; Aerosol Robotic Network
• Online Access: https://doi.org/10.3390/atmos13071080; https://doaj.org/article/fcb4638edb344a70aaf6c3120ff31ee2

Aerosol Optical Depth (AOD) is a key parameter in defining the characteristics of atmospheric aerosols, evaluating atmospheric pollution, and studying aerosol radiative climate effects. However, a large amount of the AOD data obtained by satellite remote sensing are missing due to cloud cover and other factors. To obtain AOD data with continuous distribution in space, this study considers the spatial and temporal correlation of AOD and proposes a spatio-temporal weighted filling method based on a sliding window to supply the missing AOD data blocks. The method uses the semivariogram and autocorrelation function to judge the spatial and temporal correlation of AOD and uses the AOD spatial autocorrelation threshold as the sliding window size, and then it builds a spatio-temporal weighted model for each window to fill in the missing values. We selected the area with full values for simulation. The results show that the accuracy of this method has been significantly improved compared with the mean filling method. The <semantics> R 2 </semantics> reaches 0.751, the <semantics> R M S E </semantics> is 0.021, and the filling effect is smoother. Finally, this method was used to fill in the missing values of the MultiAngle Implementation of Atmospheric Correction (MAIAC) AOD in the Beijing–Tianjin–Hebei region in 2019, and AErosol RObotic NETwork (AERONET) AOD was used as the true value for testing. The results show that the filled AOD has a high correlation with AERONET AOD, the <semantics> R 2 </semantics> is 0.785, and the <semantics> R M S E </semantics> is 0.120. A summary of the AOD values of the 13 cities in the Beijing–Tianjin–Hebei region shows that the values in the first and third quarters are higher than those in the second and fourth quarters, with the highest AOD value in March and the second highest in August; among the 13 cities, the AOD values in Chengde and Zhangjiakou are lower than those in the other cities.