MODIS Collection 6.1 aerosol optical depth products over land and ocean: validation and comparison

被引:255
作者
Wei, Jing [1 ]
Li, Zhanqing [1 ,2 ]
Peng, Yiran [3 ]
Sun, Lin [4 ]
机构
[1] Beijing Normal Univ, Coll Global Change & Earth Syst Sci, State Key Lab Remote Sensing Sci, Beijing, Peoples R China
[2] Univ Maryland, Earth Syst Sci Interdisciplinary Ctr, Dept Atmospher & Ocean Sci, College Pk, MD USA
[3] Tsinghua Univ, Dept Earth Syst Sci, Minist Educ, Key Lab Earth Syst Modeling, Beijing, Peoples R China
[4] Shandong Univ Sci & Technol, Coll Geomat, Qingdao, Peoples R China
基金
美国国家科学基金会; 国家重点研发计划;
关键词
MODIS; Collection; 6.1; AERONET Level 3 Version 2.0; DT; DB; DTB; REFLECTANCE; ALGORITHM; PM2.5;
D O I
10.1016/j.atmosenv.2018.12.004
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Recently, the newest Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6.1 (C6.1) aerosol optical depth (AOD) products were available with various refinements and improvements made to both the radiation calibration and Dark Target (DT) and Deep Blue (DB) algorithms. A combined DT and DB dataset (DTB) was also added based on piecewise fixed thresholds using the Normalized Difference Vegetation Index (NDVI) for taking advantage of one's merits. This study provides a cross-comparison and evaluation of these Terra MODIS aerosol products with reference to the enhanced ground-based AOD measurements by the Aerosol Robotic Network (AERONET) Level 3 Version 2.0 data at 384 ground stations. Their absolute and relative performance are evaluated in the period of 2013-2017 among the products, as well as between the current (C6.1) and previous (C6) releases. In general, the C6.1 aerosol products are found to be superior over the C6 products for three datasets from all scales, but the differences and improvements are rather non-uniform that varies with region. Overall, the DB AOD products show the best performance in most regions at about half of the sites, especially in Europe and North America. Meanwhile, besides bright surfaces (i.e., deserts and arid/semi-arid areas), DB products match more closely with the AERONET AODs than that of DT over medium or densely vegetated areas. The dependences of retrieval errors illustrate that the performance of three datasets deteriorates as surface reflectance, elevation and aerosol loading increase. However, the DB algorithm remains relatively more stable and less affected by changes in atmospheric and surface conditions. While the merged product using NDVI has some improvements over individual ones in general, worse performance is also shown in many cases. A more optimal method is thus wanting.
引用
收藏
页码:428 / 440
页数:13
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