Knowledge Resource Center for Ecological Environment in Arid Area
DOI | 10.1002/jgrd.50712 |
Enhanced Deep Blue aerosol retrieval algorithm: The second generation | |
Hsu, N. C.1; Jeong, M. -J.2; Bettenhausen, C.1,3; Sayer, A. M.1,4; Hansell, R.1,5; Seftor, C. S.1,3; Huang, J.5,6; Tsay, S. -C.1 | |
通讯作者 | Hsu, N. C. |
来源期刊 | JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
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ISSN | 2169-897X |
EISSN | 2169-8996 |
出版年 | 2013 |
卷号 | 118期号:16页码:9296-9315 |
英文摘要 | The aerosol products retrieved using the Moderate Resolution Imaging Spectroradiometer (MODIS) collection 5.1 Deep Blue algorithm have provided useful information about aerosol properties over bright-reflecting land surfaces, such as desert, semiarid, and urban regions. However, many components of the C5.1 retrieval algorithm needed to be improved; for example, the use of a static surface database to estimate surface reflectances. This is particularly important over regions of mixed vegetated and nonvegetated surfaces, which may undergo strong seasonal changes in land cover. In order to address this issue, we develop a hybrid approach, which takes advantage of the combination of precalculated surface reflectance database and normalized difference vegetation index in determining the surface reflectance for aerosol retrievals. As a result, the spatial coverage of aerosol data generated by the enhanced Deep Blue algorithm has been extended from the arid and semiarid regions to the entire land areas. In this paper, the changes made in the enhanced Deep Blue algorithm regarding the surface reflectance estimation, aerosol model selection, and cloud screening schemes for producing the MODIS collection 6 aerosol products are discussed. A similar approach has also been applied to the algorithm that generates the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Deep Blue products. Based upon our preliminary results of comparing the enhanced Deep Blue aerosol products with the Aerosol Robotic Network (AERONET) measurements, the expected error of the Deep Blue aerosol optical thickness (AOT) is estimated to be better than 0.05+20%. Using 10 AERONET sites with long-term time series, 79% of the best quality Deep Blue AOT values are found to fall within this expected error. |
英文关键词 | aerosol satellite retrieval |
类型 | Article |
语种 | 英语 |
国家 | USA ; South Korea |
收录类别 | SCI-E |
WOS记录号 | WOS:000324933900037 |
WOS关键词 | RESOLUTION IMAGING SPECTRORADIOMETER ; LAND SURFACES ; OPTICAL DEPTH ; MODIS ; POLARIZATION ; CAPABILITIES ; REFLECTANCE ; POLLUTION ; DUST |
WOS类目 | Meteorology & Atmospheric Sciences |
WOS研究方向 | Meteorology & Atmospheric Sciences |
资源类型 | 期刊论文 |
条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/178418 |
作者单位 | 1.NASA, Goddard Space Flight Ctr, Greenbelt, MD 20771 USA; 2.Gangneung Wonju Natl Univ, Gangneung City, South Korea; 3.Sci Syst & Applicat Inc, Lanham, MD USA; 4.Univ Space Res Assoc, Goddard Earth Sci Technol & Res, Greenbelt, MD USA; 5.UMD, Earth Syst Sci Interdisciplinary Ctr, College Pk, MD USA; 6.NOAA, NESDIS, Ctr Satellite Applicat & Res, College Pk, MD USA |
推荐引用方式 GB/T 7714 | Hsu, N. C.,Jeong, M. -J.,Bettenhausen, C.,et al. Enhanced Deep Blue aerosol retrieval algorithm: The second generation[J],2013,118(16):9296-9315. |
APA | Hsu, N. C..,Jeong, M. -J..,Bettenhausen, C..,Sayer, A. M..,Hansell, R..,...&Tsay, S. -C..(2013).Enhanced Deep Blue aerosol retrieval algorithm: The second generation.JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,118(16),9296-9315. |
MLA | Hsu, N. C.,et al."Enhanced Deep Blue aerosol retrieval algorithm: The second generation".JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES 118.16(2013):9296-9315. |
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