Retrieval of aerosol single scattering albedo using joint satellite and surface visibility measurements
Retrieval of aerosol single scattering albedo using joint satellite and surface visibility measurements
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DOI：
10.1016/j.rse.2023.113654
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发表时间：
2023-08
影响因子：
13.5
通讯作者：
Yueming Dong;Jing Li;Xing-Guang Yan;Chong Li;Zhongjing Jiang;Changrui Xiong;Liang Chang;Lu Zhang;Tong Ying;Zhenyu Zhang
中科院分区：
文献类型：
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作者：
Yueming Dong;Jing Li;Xing-Guang Yan;Chong Li;Zhongjing Jiang;Changrui Xiong;Liang Chang;Lu Zhang;Tong Ying;Zhenyu Zhang
气溶胶单次散射反照率（SSA）测量的散射消光比是测定气溶胶辐射效应的关键参数。然而，由于现有的大多数无源卫星传感器（如MODIS）仅提供大气顶部反射太阳辐射（TOA）的测量值，仅能够在假定SSA的基础上检索气溶胶光学深度（AOD），因此从卫星平台上检索SSA受到限制。在本研究中，我们开发了一种基于机器学习的算法，通过联合地表能见度和卫星辐射测量来检索SSA。在气象条件等辅助信息的作用下，地面能见度可作为柱AOD的代表。我们将MODIS测量的TOA视反射率与地面能见度以及其他辅助参数相结合，反演了全球6000多个能见度站点的SSA。2010 - 2019年的验证结果与AERONET检索的SSA具有较高的一致性，日、月和季节检索的SSA均表现出较高的相关性，分别为0.68、0.96和0.97。日RMSE、月RMSE和季节RMSE分别为0.044、0.012和0.011。日检索的平均绝对偏差（MAB）为0.031,62%的样本落在±0.03的不确定区间内。单克隆抗体的月值和季节值均降至0.01以下。超过97%的月度和季节性检索在±0.03的误差范围内。我们的工作产生了一个广泛覆盖陆地的全球气溶胶SSA数据集，可用于验证和改进气候模式以及气溶胶辐射强迫的估计。
Aerosol single scattering albedo (SSA) measuring the ratio of scattering to extinction is a critical parameter in determining aerosol radiative effect. However, the retrieval of SSA from satellite platforms is limited because most existing passive satellite sensors such as Moderate Resolution Imaging Spectroradiometer (MODIS) only provide the measurements of reflected solar radiation at the top of the atmosphere (TOA), which are only capable of retrieving aerosol optical depth (AOD) on the basis of assumed SSA. In this study, we develop a machine learning based algorithm to retrieve SSA using joint surface visibility and satellite radiation measurements. With ancillary information such as meteorological condition, surface visibility can be regarded as a proxy of column AOD. By combining MODIS measured TOA apparent reflectance with ground visibility as well as other auxiliary parameters, we retrieve SSA at over 6000 visibility stations worldwide. The validation results during the period from 2010 to 2019 show high consistency with AERONET retrieved SSA, with daily, monthly, and seasonal retrievals all exhibiting high correlations of 0.68, 0.96, and 0.97, respectively. Daily, monthly, and seasonal RMSE values are 0.044, 0.012, and 0.011, respectively. The mean absolute bias (MAB) of daily retrievals is 0.031 and 62% of the samples fall within the uncertainty interval of ±0.03. Monthly and seasonal MAB values decrease to below 0.01. Over 97% of the monthly and seasonal retrievals are within the error envelope of ±0.03. Our work generates a global aerosol SSA dataset with extensive coverage over land, which can be used for validating and improving climate models and the estimation of aerosol radiative forcing.