The single scattering albedo (SSA) of aerosol particles is one of the key variables that determine aerosol radiative forcing. Herein, an Algorithm for the retrieval of Single scattering albedo over Land (ASL) is proposed for application to full-disk data from the advanced Himawari imager (AHI) sensor flying on board the Himawari-8 satellite. In this algorithm, an atmospheric radiative transfer model known as the USM (the top of the atmosphere reflectance as the sum of Un-scattered, Single-scattered, and Multiple-scattered components) is used to calculate the SSA instead of predetermining the aerosol model; the USM is constrained by the surface bidirectional reflectance distribution function shape and aerosol optical depth (AOD) in the retrieval process. Combining two consecutive observations and a 2 * 2 pixel window, the optimal estimation algorithm is adopted to obtain the optimal solution for the aerosol SSA. These SSA results are evaluated by comparing with aerosol robotic network (AERONET) data. Linear regression shows that SSA_ASL = 0.60*SSS_AERONET + 0.38, with a correlation coefficient (0.7284), mean absolute error (0.0319), mean bias error (0.00324), root mean square error (0.0427), and ~80.11% of the ASL SSA data within an uncertainty of ±0.05 of the AERONET data. A comparison of the ASL SSA products with collocated Himawari-8 SSA products (Version 03, officially released by the Japan Meteorological Agency (JMA), referred to herein as JMA SSA) shows that the accuracy of the ASL SSA is better than that of the JMA SSA products. For the SSA retrieval in large AODs (>0.4), the validation metrics vs. AERONET data are better.

气溶胶颗粒的单次散射反照率（SSA）是决定气溶胶辐射强迫的关键变量之一。本文提出了一种陆地单散射反照率 (ASL) 检索算法，用于应用于 Himawari-8 卫星上飞行的先进 Himawari 成像仪 (AHI) 传感器的全盘数据。在该算法中，使用称为 USM 的大气辐射传输模型（大气顶部反射率作为非散射、单散射和多散射分量的总和）来计算 SSA，而不是预先确定气溶胶模型; USM在反演过程中受到表面双向反射分布函数形状和气溶胶光学深度（AOD）的约束。结合两次连续观测和2*2像素窗口，采用最优估计算法获得气溶胶SSA的最优解。这些 SSA 结果是通过与气溶胶机器人网络 (AERONET) 数据进行比较来评估的。线性回归显示 SSA _ASL = 0.60*SSS _AERONET + 0.38，相关系数 (0.7284)、平均绝对误差 (0.0319)、平均偏差误差 (0.00324)、根均值平方误差 (0.0427)，约 80.11% 的 ASL SSA 数据，误差范围为 AERONET 数据的 ±0.05。 ASL SSA产品与配套的Himawari-8 SSA产品（日本气象厅（JMA）正式发布的03版，以下简称JMA SSA）的比较表明，ASL SSA的精度优于ASL SSA的精度。 JMA SSA 产品。对于大型 AOD (>0.4) 中的 SSA 检索，验证指标与 AERONET 数据相比更好。