## 4 Experimental Results and Analysis  
### Assessment of the Completeness of Merged AOD  
A core objective of the GL-BME fusion framework is to maximally ameliorate the overall missing satellite-derived AOD products. Primarily, we quantitatively assess the spatial completeness of the original satellite-based and merged AOD datasets using the percentage of the number of pixels with valid AOD values over the experiment region. Figure 5 shows a comparison of the daily averaged AOD spatial completeness ratio among the original Himawari-8 AHI L2 AOD, merged AOD via only AHI AOD, and merged AOD via AHI, MODIS, and CALIOP AOD. The overall averaged spatial coverage of merged AOD after the GL-BME fusion process obviously improves from 20.3% to 67.6% compared to the original AOD. It can be found that the introduction of LEO sensors could additionally contribute to the spatial coverage improvement, approximately from 48.3% to 67.5%, which indicates that the introduction of LEO satellite sensors into the GL-BME fusion algorithm could further enhance the spatial completeness of the merged AOD. Moreover, the spatial completeness of the merged AOD exceeds 65% for almost half of the experimental period and even reaches up to 80% in a few days. The spatial distributions of annually averaged completeness for the original Himawari-8 AHI AOD data and merged AOD data are presented for comparison in Figure 6. As depicted in Figure 6a,b, the annually averaged completeness of the original AHI AOD data ranges from 0 to 39.2% with a median of 20.1%, whereas the annually averaged completeness of merged AOD data ranges from 41.3% to 98.2% with a median of 65.1%. Remarkably, the annually averaged completeness of the original Himawari-8 AHI AODs and merged AODs follows a consistent spatial variability pattern; that is, the coverage ratio is lowest in the southwest plateau region, followed by some high-latitude areas. As demonstrated in Figure 6c, there exists  
Figure 4: **(a,b)** Experimental (circles) and fitted theoretical (solid line) covariance shown as a function of the spatial lag (0 to 250 km) and the temporal lag, respectively. The exponential model fitting is shown as red solid line, the spherical model fitting is shown as blue solid line, and the green solid line represents the Gaussian model fitting. **(c)** Experimental (gray solid dots) and fitted nested theoretical spatiotemporal covariance (color). The spatial lag (0 to 250 km) is shown on the left axis, and the temporal lag (0 to 200 min) is shown on the right axis and the spatiotemporal covariance on the vertical axis. Experimental covariance is calculated from the point pairs at specific distances according to AOD datasets after spatiotemporal trend removal, which is based on datasets from May 2017.  
substantial improvement in the AOD completeness in the experimental regions, especially in the south of Mongolia and north of China, far from the Himawari-8 satellite nadir. The probable reason is that the original AHI AOD products periodically have intrinsic data blanks over these regions due to the combination of large viewing zenith and high surface reflectance, which could be well recovered by complementary AOD observations derived from LEO satellites.