Aerosols are one of the important parameters affecting the atmospheric radiation balance. They have a wide range of sources and a relatively short life cycle in the atmosphere, exhibiting significant spatiotemporal variability, which makes it particularly difficult to accurately quantify aerosol information in the atmosphere. Traditional multispectral satellite detection signals only provide single-intensity radiation information. This signal is more sensitive to surface information and contains weaker aerosol information, which leads to limitations in the types and accuracy of aerosol parameters that can be retrieved. Compared to hyperspectral remote sensing methods, which increase the number of bands, multi-angle and polarization play an important role in improving aerosol retrieval due to their unique advantages. Multi-angle polarization sensors combine angle and polarization parameters, enabling more accurate retrieval of atmospheric and surface parameters. Given the significant advantages of multi-angle polarization data, observation angles, and polarization are crucial parameters in aerosol retrieval, which makes it particularly important to analyze their effect on aerosol retrieval. We use visible-near infrared band satellite observation data simulated based on polarization simulation technology and the official generalized retrieval of aerosol and surface properties (GRASP) program module to study the aerosol optical thickness retrieval of the simulated data. By comparing and analyzing the retrieval results under different numbers of observation angles and polarization band states, we conduct an in-depth study of the impact of observation angle numbers and polarization channel settings on aerosol optical thickness retrieval, aiming to provide references for the parameter design of multi-angle polarization sensors.

First, polarization simulation technology is used to model the radiation transfer process of sunlight, which addresses the lack of angle and polarization observation data. A simulated dataset is established based on surface and atmospheric parameter characteristics provided by moderate-resolution imaging spectroradiometer (MODIS), hyper-angular rainbow polarimeter #2 (HARP2), polarization and directionality of the earth’s reflectances-3 (POLDER3), and GRASP. The bidirectional surface reflectance distribution function model, Ross-Li, and the bidirectional surface polarized reflectance distribution function model, Maignan, are used to simulate the surface contribution during the radiation transfer process. The aerosol model is simulated using a bimodal normal particle size distribution method, while the atmospheric contribution during the radiation transfer process is modeled using the second simulation of the satellite signal in the solar spectrum code (6SV) model. Finally, considering land-atmosphere coupling effects and satellite observation errors, the intensity and polarization of satellite observation data are simulated under more realistic conditions. The official GRASP inversion algorithm is then applied, using the multi-pixel inversion module for aerosol inversion research. Based on the inversion results, we evaluate the observation angle and polarization dependencies in aerosol remote sensing.

By analyzing the inversion accuracy with different numbers of polarization channels, we find that as the number of channels increases, the Pearson correlation coefficient (R) rises from 0.835 for non-polarized channels to 0.876 for fully polarized channels. The root mean square error (RMSE) and mean absolute error (MAE) decrease from 0.124 and 0.098, respectively, to 0.076 and 0.059. The proportion of points within the expected error (EE) range increases from 69% to 91% (Fig. 3). These results indicate that increasing the number of polarization channels significantly enhances aerosol inversion accuracy. However, the overall trend of inversion accuracy improvement becomes more gradual, which reveals that there is an upper limit to the enhancement effect of polarization. For specific polarization combinations, the higher sensitivity of shorter wavelengths to aerosols means that better inversion results are mainly concentrated in combinations with shorter wavelengths. In contrast, for longer wavelength combinations such as “565 nm, 670 nm” (Fig. 5); “490, 565, 670 nm” (Fig. 6); “490, 565, 670, 865 nm” (Fig. 7); and “490, 565, 670, 865, 1020 nm” (Fig. 8), a significant decrease in inversion accuracy is observed. By analyzing the aerosol optical depth (AOD) scatter verification results under different observation modes, we hold that as the number of observation angles increases from 1 to 14, the R rises from 0.378 to 0.872, RMSE decreases from 0.234 to 0.095, and MAE drops from 0.194 to 0.075. The proportion of points within the expected error range increases from 28.46% to 82.9% (Fig. 9). These results demonstrate that the aerosol inversion capability of a multi-angle polarization payload improves significantly with an increasing number of observation angles. However, as the number of observation angles increases, the improvement in the inversion effect becomes less pronounced (Fig. 10). This is because, while the increase in the number of angles significantly enhances the information volume, the effective observation volume gradually saturates, and new errors are introduced. As a result, the aerosol inversion accuracy tends to stabilize as the number of observation angles increases, and in some cases, the inversion accuracy may even decrease despite the addition of more angles.

We employ simulated multi-angle and multi-spectral intensity and polarization data to retrieve AOD using the GRASP inversion algorithm under varying numbers of observation angles and polarization bands. The retrieved AOD is compared with the true AOD to assess consistency. Evaluation metrics, including the R, RMSE, MAE, and expected error, are used to analyze the dependence of multi-angle polarization aerosol inversion on the number of observation angles and polarization bands. The results indicate that the aerosol inversion capability improves with an increasing number of polarization channels, but the trend of accuracy enhancement becomes more gradual, which suggests an upper limit to the improvement from additional polarization channels. Additionally, due to the higher sensitivity of shorter wavelengths to aerosols, inversion results are more accurate when polarization channels are set at shorter wavelengths rather than longer ones. Furthermore, as the number of observation angles increases, the consistency between the retrieved AOD and the true AOD improves significantly, which reveals the enhanced aerosol inversion capability of multi-angle polarization payloads. However, as the number of observation angles continues to increase, the effective observation information saturates, and new errors are introduced, which causes the improvement in inversion accuracy to plateau.