Assessment and Improvement of MISR Angstrom Exponent and Single-Scattering Albedo Products Using AERONET Data in China
Assessment and Improvement of MISR Angstrom Exponent and Single-Scattering Albedo Products Using AERONET Data in China
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中国利用AERONET数据评估和改进MISR安斯特罗姆指数和单散射反照率产品
DOI：
10.3390/rs9070693
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发表时间：
2017-07
期刊：
影响因子：
5
通讯作者：
Si Yidan
中科院分区：
文献类型：
--
作者：
Si Yidan
绘制颗粒污染物的组分、尺寸和吸收/散射特性在环境和公共卫生领域具有极大的兴趣。虽然多角度成像分光辐射计（MISR）可以检测到更多的气溶胶微物理特性比大多数其他星载传感器，埃指数（AE）和单次散射散射（SSA）产品没有被广泛使用或作为强大的气溶胶光学厚度（AOD）产品。本研究的重点是使用AERONET（AERONET）数据验证2004年至2014年中国的MISR AE和SSA数据。MISR数据的全国平均值（1.08）比AERONET数据低0.095。然而，MISR SSA平均值（0.99）显著高于AERONET（0.89）。在这项研究中，我们开发了一种方法来改善AE和SSA通过缩小MISR混合物的选择，通过引入以下组阈值从11年的AERONET数据集获得：最小值和最大值（对于MISR_Imp_All方法）和平均值的前10%和后10%（对于MISR_Imp_10%）。总的来说，我们改进的AE值更接近AERONET AE值，并且其他样本（MISR_Imp_All：28.04%和64.72%，MISR_Imp_10%：34.11%和73.13%）的绝对差异小于0.1和0.3（由预期误差检验定义，例如，EE_0.1）与原MISR产品（18.46%和50.23%）相比。对于SSA产品，我们的方法还将平均值、EE_0.05和EE_0.1分别从0.99、16.13%和56.45%（MISR原始产品）提高到0.96、40.32%和70.97%（MISR_Imp_All）以及0.94、54.84%和90.32%（MISR_Imp_10%）。
Mapping the components, size, and absorbing/scattering properties of particle pollution is of great interest in the environmental and public health fields. Although the Multi-angle Imaging SpectroRadiometer (MISR) can detect a greater number of aerosol microphysical properties than most other spaceborne sensors, the Angstrom exponent (AE) and single-scattering albedo (SSA) products are not widely utilized or as robust as the aerosol optical depth (AOD) product. This study focused on validating MISR AE and SSA data using AErosol RObotic NETwork (AERONET) data for China from 2004 to 2014. The national mean value of the MISR data (1.08) was 0.095 lower than that of the AERONET data. However, the MISR SSA average (0.99) was significantly higher than that of AERONET (0.89). In this study, we developed a method to improve the AE and SSA by narrowing the selection of MISR mixtures via the introduction of the following group thresholds obtained from an 11-year AERONET dataset: minimum and maximum values (for the method of MISR_Imp_All) and the top 10% and bottom 10% of the averaged values (for MISR_Imp_10%). Overall, our improved AE values were closer to the AERONET AE values, and additional samples (MISR_Imp_All: 28.04% and 64.72%, MISR_Imp_10%: 34.11% and 73.13%) had absolute differences of less than 0.1 and 0.3 (defined by the expected error tests, e.g., EE_0.1) compared with the original MISR product (18.46% and 50.23%). For the SSA product, our method also improved the mean, EE_0.05, and EE_0.1 from 0.99, 16.13%, and 56.45% (MISR original product) to 0.96, 40.32%, and 70.97% (MISR_Imp_All), and 0.94, 54.84%, and 90.32% (MISR_Imp_10%), respectively.
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影响因子：
10.4
作者：
Meng X;Ma Y;Chen R;Zhou Z;Chen B;Kan H
通讯作者：
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影响因子：
10.4
作者：
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通讯作者：
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影响因子：
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作者：
Kang Na;Kumar K. Raghavendra;Yu Xingna;Yin Yan
通讯作者：
Yin Yan
DOI：
10.1016/j.jqsrt.2014.08.012
发表时间：
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影响因子：
2.3
作者：
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通讯作者：
B. Yin;Q. Min;E. Joseph
影响因子：
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作者：
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