globalchange  > 影响、适应和脆弱性
DOI: 10.1002/2016JD024859
论文题名:
An enhanced VIIRS aerosol optical thickness (AOT) retrieval algorithm over land using a global surface reflectance ratio database
作者: Zhang H.; Kondragunta S.; Laszlo I.; Liu H.; Remer L.A.; Huang J.; Superczynski S.; Ciren P.
刊名: Journal of Geophysical Research: Atmospheres
出版年: 2016
卷: 121, 期:18
起始页码: 10717
结束页码: 10738
语种: 英语
英文关键词: aerosol optical thickness ; remote sensing ; retrieval ; satellite ; Suomi-NPP ; VIIRS
Scopus关键词: AERONET ; aerosol ; algorithm ; database ; global perspective ; ground-based measurement ; MODIS ; remote sensing ; spatial resolution ; Suomi NPP ; surface reflectance ; top of atmosphere ; VIIRS
英文摘要: The Visible/Infrared Imager Radiometer Suite (VIIRS) on board the Suomi National Polar-orbiting Partnership (S-NPP) satellite has been retrieving aerosol optical thickness (AOT), operationally and globally, over ocean and land since shortly after S-NPP launch in 2011. However, the current operational VIIRS AOT retrieval algorithm over land has two limitations in its assumptions for land surfaces: (1) it only retrieves AOT over the dark surfaces and (2) it assumes that the global surface reflectance ratios between VIIRS bands are constants. In this work, we develop a surface reflectance ratio database over land with a spatial resolution 0.1° × 0.1° using 2 years of VIIRS top of atmosphere reflectances. We enhance the current operational VIIRS AOT retrieval algorithm by applying the surface reflectance ratio database in the algorithm. The enhanced algorithm is able to retrieve AOT over both dark and bright surfaces. Over bright surfaces, the VIIRS AOT retrievals from the enhanced algorithm have a correlation of 0.79, mean bias of −0.008, and standard deviation (STD) of error of 0.139 when compared against the ground-based observations at the global AERONET (Aerosol Robotic Network) sites. Over dark surfaces, the VIIRS AOT retrievals using the surface reflectance ratio database improve the root-mean-square error from 0.150 to 0.123. The use of the surface reflectance ratio database also increases the data coverage of more than 20% over dark surfaces. The AOT retrievals over bright surfaces are comparable to MODIS Deep Blue AOT retrievals. ©2016. American Geophysical Union. All Rights Reserved.
资助项目: "This work is supported by the NOAA JPSS program. The authors thank the MODIS team and AERONET principal investigators and site managers for providing the data used in this work. The contents in this paper are solely the opinions of the authors and do not constitute a statement of policy, decision, or position on behalf of NOAA or the U.S. Government. The data used in this paper can be requested from Istvan Laszlo (Istvan.Laszlo@noaa.gov) or Shobha Kondragunta (Shobha.Kondragunta@noaa.gov).
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/62820
Appears in Collections:影响、适应和脆弱性
气候减缓与适应

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作者单位: I. M. Systems Group at NOAA, College Park, MD, United States; NOAA NESDIS STAR, College Park, MD, United States; University of Maryland College Park, College Park, MD, United States; Joint Center for Earth Systems Technology (JCET), University of Maryland Baltimore County, Baltimore, MD, United States; Systems Research Group, College Park, MD, United States

Recommended Citation:
Zhang H.,Kondragunta S.,Laszlo I.,et al. An enhanced VIIRS aerosol optical thickness (AOT) retrieval algorithm over land using a global surface reflectance ratio database[J]. Journal of Geophysical Research: Atmospheres,2016-01-01,121(18)
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