A multi-angle and polarization-based retrieval algorithm for aerosol layer height of smoke and dust

The vertical distribution of aerosols in the atmosphere governs their interactions with solar radiation and cloud processes, and is therefore a key factor influencing their climatic and environmental effects. Existing passive remote sensing methods for retrieving aerosol layer height (ALH) largely rely on a single observational dimension (e.g., spectral or multi-angle information), which provides limited constraints on layer height under complex aerosol conditions and consequently restricts retrieval accuracy and applicability. To address this issue, this study extends conventional spectral approaches by incorporating multi-angle polarimetric observations. By exploiting the high sensitivity of polarization signals to the differences between molecular Rayleigh scattering and aerosol scattering, as well as the capability of multi-angle measurements to sample a broader range of scattering angles, the sensitivity to aerosol vertical structure is significantly enhanced. Based on a vector radiative transfer model combined with an information content analysis method, the contributions of multi-angle and polarization information to ALH retrieval are systematically evaluated. The results show that, compared with radiance-only observations, multi-angle polarimetric measurements substantially increase the Degrees of Freedom for Signal (DFS) of the retrieval system, thereby improving the accuracy of ALH retrievals. Building on this, an optimal estimation method is developed using multi-angle polarimetric observations from the HARP2 (Hyper-Angular Rainbow Polarimeter-2) instrument aboard the PACE (Plankton, Aerosol, Cloud, ocean Ecosystem) satellite. The retrieval results are validated against Lidar observations from ATLID (Atmospheric Lidar) onboard the EarthCARE (Earth Clouds, Aerosols and Radiation Explorer) mission. Statistical analysis indicates that, for all collocated samples, the HARP2 retrievals achieve a root mean square error (RMSE) of 1.03 km, significantly lower than the 1.40 km obtained from the TROPOMI (TROPOspheric Monitoring Instrument) product, with a near-zero mean bias (−0.07 km), demonstrating good overall consistency. For smoke cases, the RMSE is 1.12 km, while for dust cases it further decreases to 0.92 km. Moreover, in a typical dust transport event, the proportion of retrieval errors smaller than 1 km reaches 84.5 %, highlighting the significant accuracy advantage of multi-angle polarimetric observations in aerosol layer height retrieval.