A consistent aerosol optical depth (AOD) dataset over mainland China by integration of several AOD products
A consistent aerosol optical depth (AOD) dataset over mainland China by integration of several AOD products
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DOI：
10.1016/j.atmosenv.2015.05.023
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发表时间：
2015-08
影响因子：
5
通讯作者：
Hengchao Xu;J. Guang;Yong Xue;G. Leeuw;Y. Che;Jianping Guo;Xingwei He;T. K. Wang
中科院分区：
文献类型：
--
作者：
Hengchao Xu;J. Guang;Yong Xue;G. Leeuw;Y. Che;Jianping Guo;Xingwei He;T. K. Wang
中分辨率成像光谱仪（MODIS）、多角度成像光谱仪（MISR）和海景宽视场传感器（SeaWiFS）提供了陆地和海洋上空经验证的气溶胶光学厚度（AOD）产品。然而，由这些卫星中的每一个提供的AOD的值可能会显示空间和时间的差异，由于仪器的特性和用于每个仪器的气溶胶反演算法。在这篇文章中，我们提出了一种方法，以产生一个AOD数据集的基础上，融合不同的仪器和/或算法提供的数据在亚洲的2007年。首先，通过与来自AERONET和中国气溶胶遥感网（CARSNET）的地面AOD数据进行比较，计算了每个卫星获得的AOD产品的偏差。然后，使用最大似然估计（MLE）方法，使用从与原始AOD产品的精度相关联的均方根误差（RMSE）导出的权重来组合这些多个AOD产品。通过与CARSNET的AOD数据进行比较，验证了原始和合并的AOD数据集。结果表明，合并后的AOD数据集的平均偏差误差（MBE）和平均绝对误差（MAE）不大于任何原始AOD产品。此外，对于合并的AOD数据集，没有数据的像素的分数显著小于任何原始产品的像素的分数，从而增加了空间覆盖范围。合并后的AOD数据集的可检索区域的比例约为50%，MISR，SeaWiFS，MODIS-DT和MODIS-DB算法的可检索区域的比例在5%和20%之间。
The Moderate Resolution Imaging Spectroradiometer (MODIS), the Multiangle Imaging Spectroradiometer (MISR) and the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) provide validated aerosol optical depth (AOD) products over both land and ocean. However, the values of the AOD provided by each of these satellites may show spatial and temporal differences due to the instrument characteristics and aerosol retrieval algorithms used for each instrument. In this article we present a method to produce an AOD data set over Asia for the year 2007 based on fusion of the data provided by different instruments and/or algorithms. First, the bias of each satellite-derived AOD product was calculated by comparison with ground-based AOD data derived from the AErosol RObotic NETwork (AERONET) and the China Aerosol Remote Sensing NETwork (CARSNET) for different values of the surface albedo and the AOD. Then, these multiple AOD products were combined using the maximum likelihood estimate (MLE) method using weights derived from the root mean square error (RMSE) associated with the accuracies of the original AOD products. The original and merged AOD dataset has been validated by comparison with AOD data from the CARSNET. Results show that the mean bias error (MBE) and mean absolute error (MAE) of the merged AOD dataset are not larger than that of any of the original AOD products. In addition, for the merged AOD dataset the fraction of pixels with no data is significantly smaller than that of any of the original products, thus increasing the spatial coverage. The fraction of retrievable area is about 50% for the merged AOD dataset and between 5% and 20% for the MISR, SeaWiFS, MODIS-DT and MODIS-DB algorithms.