Reflectance Correction and Retrieval of Cloud Optical Thickness and Effective Radius Using GF-5(02) POSP Observations

Abstract

Clouds are essential components of the weather and climate system, influencing it by altering the radiation balance and participating in the hydrological cycle. Cloud optical thickness (COT) and cloud effective radius (CER) are critical parameters describing cloud optical and microphysical properties. This study investigates the reflectance characteristics of the particulate observing scanning polarimeter (POSP) onboard GaoFen-5(02) satellite [POSP/GF-5(02)] and proposes a reflectance correction method based on the unified linearized vector radiative transfer model (UNL-VRTM). Using the corrected reflectance, COT and CER are retrieved through an optimized dual-channel method (0.865– $2.25~\mu $ m), with channel selection guided by sensitivity analysis. The retrieval results are further assessed with Moderate Resolution Imaging Spectroradiometer (MODIS) products. Results show that, under the current correction method, the original POSP reflectance used for the cloud target is underestimated by 15.61%, 51.59%, and 44.38% at 0.865, 1.61, and $2.25~\mu $ m, respectively. Region case studies demonstrate that after reflectance correction, the fractions of retrievals within the predefined accuracy thresholds increase by an average of 61.83% for CER and 47.08% for COT. Further case analysis shows that retrieval accuracy varies with cloud field heterogeneity and surface complexity, with CER accuracy decreasing by 50.56% relative to a homogeneous cloud field and COT accuracy decreasing by 13.23% relative to dark ocean surfaces. These results indicate that the proposed reflectance correction framework substantially enhances the accuracy of cloud property retrievals from POSP observations, providing improved capability for cloud remote sensing and supporting further studies of weather and climate processes.