Validation of MODIS aerosol optical depth product over China using CARSNET measurements
Validation of MODIS aerosol optical depth product over China using CARSNET measurements
复制标题
使用 CARSNET 测量验证中国 MODIS 气溶胶光学深度产品
DOI：
10.1016/j.atmosenv.2011.08.002
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发表时间：
2011-10
影响因子：
5
通讯作者：
Che Huizheng
中科院分区：
文献类型：
--
作者：
Xie Yong;Zhang Yan;Xiaoxiong Xiong;John J. Qu;Che Huizheng
本文利用中国气溶胶遥感网（CARSNET）收集的地面测量数据，对MODIS气溶胶光学深度（AOD）反演结果进行了评价。在现阶段，MODIS Collection 5 (C5) aod通过两种不同的算法进行检索：Dark Target （DT）和Deep Blue （DB）。CARSNET aod是通过气溶胶机器人网络（AEROENT）部署的相同仪器Cimel Electronique CE-318测量得出的。通过在卫星立交桥7.5 min内将每个MODIS AOD像元（10 × 10 km2）与CARSNET AOD均值进行匹配，实现AOD的配置。MODIS/CARSNET在10个站点的4年比较（2005-2008）表明，MODIS AOD检索的性能高度依赖于下垫面。在森林和草原地区，MODIS DT AODs平均比CARSNET AODs低6-30%，而在城市地区和沙漠地区，MODIS DT AODs平均比CARSNET AODs高54%，比CARSNET AODs高95%。在森林和草原地区，超过50%的MODIS DT AODs在预期误差范围内。MODIS DT对市区小AOD有高估的倾向。在高植被区，对小AOD估计过低，对大AOD估计过高。一般说来，随着AOD值的减小，其质量也随之降低。MODIS DB能够在沙漠上检索AOD，但在CARSNET站点上有明显的低估。MODIS DB在草地上的检索效果最好，在预期误差范围内的检索率约为70%。简要讨论了MODIS AOD检索的时空配置和仪器标定的不确定性。
This study evaluates Moderate Resolution Imaging Spectroradiometer (MODIS) Aerosol Optical Depth (AOD) retrievals with ground measurements collected by the China Aerosol Remote Sensing NETwork (CARSNET). In current stage, the MODIS Collection 5 (C5) AODs are retrieved by two distinct algorithms: the Dark Target (DT) and the Deep Blue (DB). The CARSNET AODs are derived with measurements of Cimel Electronique CE-318, the same instrument deployed by the AEROsol Robotic Network (AEROENT). The collocation is performed by matching each MODIS AOD pixel (10 × 10 km2) to CARSNET AOD mean within 7.5 min of satellite overpass. Four-year comparisons (2005–2008) of MODIS/CARSNET at ten sites show the performance of MODIS AOD retrieval is highly dependent on the underlying land surface. The MODIS DT AODs are on average lower than the CARSNET AODs by 6–30% over forest and grassland areas, but can be higher by up to 54% over urban area and 95% over desert-like area. More than 50% of the MODIS DT AODs fall within the expected error envelope over forest and grassland areas. The MODIS DT tends to overestimate for small AOD at urban area. At high vegetated area it underestimates for small AOD and overestimates for large AOD. Generally, its quality reduces with the decreasing AOD value. The MODIS DB is capable of retrieving AOD over desert but with a significant underestimation at CARSNET sites. The best retrieval of the MODIS DB is over grassland area with about 70% retrievals within the expected error. The uncertainties of MODIS AOD retrieval from spatial–temporal collocation and instrument calibration are discussed briefly.
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影响因子：
4.4
作者：
Levy, Robert C.;Remer, Lorraine A.;Dubovik, Oleg
通讯作者：
Dubovik, Oleg
基于中国长江三角洲地区地面测量的气溶胶光学特性
影响因子：
5
作者：
通讯作者：
--
影响因子：
4.9
作者：
T. Knutson;S. Manabe
通讯作者：
T. Knutson;S. Manabe
影响因子：
4.8
作者：
X. Xiong;Junqiang Sun;W. Barnes
通讯作者：
X. Xiong;Junqiang Sun;W. Barnes
影响因子：
4.4
作者：
Che, Huizheng;Zhang, Xiaoye;Zhou, Tianming
通讯作者：
Zhou, Tianming