## 3 Algorithm Description
### Comparison with AERONET AOD and SSA  
Following [PERSON] et al. (2012), the AOD and SSA products are quantitatively compared with AERONET values and their accuracy is assessed using statistics of linear regression such as correlation coefficient (R), root-mean-square error (RMSE), slope (a), y-offset (b) and the Q value, which shows data points within a 30% error range. For the validation, the algorithm is used on data for the three years from 2005 to 2007 while accounting for the row anomalies of OMI. The 26 AERONET sites that have measurements in the test window are selected as shown in Table 2. The retrieved AODs within a 0.4\({}^{\circ}\)\(\times\) 0.4\({}^{\circ}\) area from the AERONET site are averaged and compared with AERONET values within the overpass time of 10 min from OMI observations. The retrieved SSAs are collocated when they are within a 0.4\({}^{\circ}\)\(\times\) 0.4\({}^{\circ}\) area regardless of observation time during the day because of the large time difference between OMI measurements and the AERONET inversion product. The AERONET SSA is valid for SZA higher than 50\({}^{\circ}\)[36] but the OMI has a local equator crossing time of about 13:45. Figure 9 compares AOD and SSA. The AODs retrieved from the developed algorithm are compared with those from AERONET observations (Figure 9a) and the OMAERUV algorithm (Figure 9b). The comparison between AODs from OMAERUV and AERONET is shown in Figure 9c and the a priori AOD, which are retrieved based on the same two-channel approach of the OMAERUV algorithm, are also compared to the OMI products (Figure 9d). The retrieved AOD shows a good correlation with the AERONET AOD with a correlation coefficient (R) of 0.71 and a Q value of 57% (Figure 9a), although the correlation is weaker than that shown in Figure 9c. Compared with the OMI AOD, retrieved AODs from the developed algorithm are mostly overestimated with a regression slope of 1.18 (Figure 9b), while the a priori AODs are highly correlated (R = 0.97). As shown in Figure 9a, the R values for HAF, dust and NA are 0.83, 0.73 and 0.80, respectively. The variation in regression line slopes from 0.56 (HAF) to 0.98 (NA) indicates uncertainties in model parameter assumptions. In the algorithm, a LUT for each aerosol type was calculated assuming a wavelength dependence of aerosol absorptivity based on the literature. [PERSON] et al. (2013) obtained the spectral variation of the imaginary refractive index for biomass smoke samples and [PERSON] et al. (2015) measured the spectral dependence of brown carbon absorptivity in the Amazon. However, the database cannot accurately  
represent the AOPs of anthropogenic aerosol over Asia. Therefore, measuring accurate AOPs over Asia in the shortwave region is essential for future work. Though the developed algorithm does not perform better than the OMI OMAERUV algorithm, it lays the foundation for improved retrieval in the future as the characterization of the optical properties of Asian aerosols improves. With the improved spatial resolution of GEMS over that of OMI, the cloud contamination can be reduced significantly. This uncertainty has a greater impact on the accuracy of SSA retrieval. Figure 10 compares the retrieved SSA with AERONET values (Figure 10a) and OMI SSA (Figure 10b). [PERSON] et al. [13] showed that 70% of OMI SSA differed by less than 0.05 from AERONET values over northeast Asia. Similarly, Figure 10c shows that 61% of OMI SSAs are within the same 0.05 difference. The Q value for the data shown in Figure 10a is generally lower than that for OMI SSA, while 95% of the retrieved SSAs differed by less than 0.05 from the OMI SSA (Figure 10b). Unlike the AOD comparison shown in Figure 9d, a priori SSAs are higher than OMI values and this difference increases with decreasing OMI SSA because of differing aerosol model assumptions. The large error in SSA retrieval could be caused by errors in classifying aerosols by type and in surface reflectance estimations. Section 5 includes a detailed discussion of retrieval uncertainties.