车亚辉等:Technical note: Intercomparison of three AATSR Level 2 (L2) AOD products over China
被阅读 567 次
2016-10-14
Technical note: Intercomparison of three AATSR Level 2 (L2) AOD products over China
作者:Che, YH (Che, Yahui)[ 1,6 ] ; Xue, Y (Xue, Yong)[ 1,2 ] ; Mei, LL (Mei, Linlu)[ 3 ] ; Guang, J (Guang, Jie)[ 3 ] ; She, L (She, Lu)[ 1,6 ] ; Guo, JP (Guo, Jianping)[ 4 ] ; Hu, YC (Hu, Yincui)[ 5 ] ; Xu, H (Xu, Hui)[ 3 ] ; He, XW (He, Xingwei)[ 1,6 ] ; Di, AJ (Di, Aojie)[ 1,6 ] ; Fan, C (Fan, Cheng)[ 1,6 ]
ATMOSPHERIC CHEMISTRY AND PHYSICS
卷: 16  期: 15  页: 9655-9674
DOI: 10.5194/acp-16-9655-2016
出版年: AUG 2 2016
 
摘要
One of four main focus areas of the PEEX initiative is to establish and sustain long-term, continuous, and comprehensive ground-based, airborne, and seaborne observation infrastructure together with satellite data. The Advanced Along-Track Scanning Radiometer (AATSR) aboard ENVISAT is used to observe the Earth in dual view. The AATSR data can be used to retrieve aerosol optical depth (AOD) over both land and ocean, which is an important parameter in the characterization of aerosol properties. In recent years, aerosol retrieval algorithms have been developed both over land and ocean, taking advantage of the features of dual view, which can help eliminate the contribution of Earth's surface to top-of-atmosphere (TOA) reflectance. The Aerosol_cci project, as a part of the Climate Change Initiative (CCI), provides users with three AOD retrieval algorithms for AATSR data, including the Swansea algorithm (SU), the ATSR-2ATSR dual-view aerosol retrieval algorithm (ADV), and the Oxford-RAL Retrieval of Aerosol and Cloud algorithm (ORAC). The validation team of the Aerosol-CCI project has validated AOD (both Level 2 and Level 3 products) and AE (angstrom ngstrom Exponent) (Level 2 product only) against the AERONET data in a round-robin evaluation using the validation tool of the AeroCOM (Aerosol Comparison between Observations and Models) project. For the purpose of evaluating different performances of these three algorithms in calculating AODs over mainland China, we introduce ground-based data from CARSNET (China Aerosol Remote Sensing Network), which was designed for aerosol observations in China. Because China is vast in territory and has great differences in terms of land surfaces, the combination of the AERONET and CARSNET data can validate the L2 AOD products more comprehensively. The validation results show different performances of these products in 2007, 2008, and 2010. The SU algorithm performs very well over sites with different surface conditions in mainland China from March to October, but it slightly underestimates AOD over barren or sparsely vegetated surfaces in western China, with mean bias error (MBE) ranging from 0.05 to 0.10. The ADV product has the same precision with a low root mean square error (RMSE) smaller than 0.2 over most sites and the same error distribution as the SU product. The main limits of the ADV algorithm are underestimation and applicability; underestimation is particularly obvious over the sites of Datong, Lanzhou, and Urumchi, where the dominant land cover is grassland, with an MBE larger than 0.2, and the main aerosol sources are coal combustion and dust. The ORAC algorithm has the ability to retrieve AOD at different ranges, including high AOD (larger than 1.0); however, the stability deceases significantly with increasing AOD, especially when AOD> 1.0. In addition, the ORAC product is consistent with the CARSNET product in winter (December, January, and February), whereas other validation results lack matches during winter.
 
通讯作者地址: Xue, Y (通讯作者)
Chinese Acad Sci, State Key Lab Remote Sensing Sci, Inst Remote Sensing & Digital Earth, Beijing 100101, Peoples R China.
通讯作者地址: Xue, Y (通讯作者)
Univ Derby, Coll Engn & Technol, Dept Comp & Math, Kedleston Rd, Derby DE22 1GB, England.
地址:
[ 1 ] Chinese Acad Sci, State Key Lab Remote Sensing Sci, Inst Remote Sensing & Digital Earth, Beijing 100101, Peoples R China
[ 2 ] Univ Derby, Coll Engn & Technol, Dept Comp & Math, Kedleston Rd, Derby DE22 1GB, England
[ 3 ] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Key Lab Digital Earth Sci, Beijing 100094, Peoples R China
[ 4 ] Chinese Acad Meteorol Sci, Ctr Atmosphere Watch & Serv, 46 Zhongguancun South Ave, Beijing 100081, Peoples R China
[ 5 ] Hebei Normal Univ, Coll Resources & Environm Sci, Hebei Key Lab Environm Change & Ecol Construct, Shijiazhuang, Hebei Province, Peoples R China
[ 6 ] Univ Chinese Acad Sci, Beijing 100049, Peoples R China