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Evaluation of VIIRS Land Aerosol Model Selection with AERONET Measurements

The Visible Infrared Imaging Radiometer Suite (VIIRS) is a next-generation polar-orbiting operational environmental sensor with a capability for global aerosol observations. Identifying land aerosol types is important because aerosol types are a basic input in retrieving aerosol optical properties f...

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Autores principales: Wang, Wei, Pan, Zengxin, Mao, Feiyue, Gong, Wei, Shen, Longjiao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5615553/
https://www.ncbi.nlm.nih.gov/pubmed/28872609
http://dx.doi.org/10.3390/ijerph14091016
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author Wang, Wei
Pan, Zengxin
Mao, Feiyue
Gong, Wei
Shen, Longjiao
author_facet Wang, Wei
Pan, Zengxin
Mao, Feiyue
Gong, Wei
Shen, Longjiao
author_sort Wang, Wei
collection PubMed
description The Visible Infrared Imaging Radiometer Suite (VIIRS) is a next-generation polar-orbiting operational environmental sensor with a capability for global aerosol observations. Identifying land aerosol types is important because aerosol types are a basic input in retrieving aerosol optical properties for VIIRS. The VIIRS algorithm can automatically select the optimal land aerosol model by minimizing the residual between the derived and expected spectral surface reflectance. In this study, these selected VIIRS aerosol types are evaluated using collocated aerosol types obtained from the Aerosol Robotic Network (AERONET) level 1.5 from 23 January 2013 to 28 February 2017. The spatial distribution of VIIRS aerosol types and the aerosol optical depth bias (VIIRS minus AERONET) demonstrate that misidentifying VIIRS aerosol types may lead to VIIRS retrieval being overestimated over the Eastern United States and the developed regions of East Asia, as well as underestimated over Southern Africa, India, and Northeastern China. Approximately 22.33% of VIIRS aerosol types are coincident with that of AERONET. The agreements between VIIRS and AERONET for fine non-absorbing and absorbing aerosol types are approximately 36% and 57%, respectively. However, the agreement between VIIRS and AERONET is extremely low (only 3.51%). The low agreement for coarse absorbing dust may contribute to the poor performance of VIIRS retrieval under the aerosol model (R = 0.61). Results also show that an appropriate aerosol model can improve the retrieval performance of VIIRS over land, particularly for dust type (R increases from 0.61 to 0.72).
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spelling pubmed-56155532017-09-30 Evaluation of VIIRS Land Aerosol Model Selection with AERONET Measurements Wang, Wei Pan, Zengxin Mao, Feiyue Gong, Wei Shen, Longjiao Int J Environ Res Public Health Article The Visible Infrared Imaging Radiometer Suite (VIIRS) is a next-generation polar-orbiting operational environmental sensor with a capability for global aerosol observations. Identifying land aerosol types is important because aerosol types are a basic input in retrieving aerosol optical properties for VIIRS. The VIIRS algorithm can automatically select the optimal land aerosol model by minimizing the residual between the derived and expected spectral surface reflectance. In this study, these selected VIIRS aerosol types are evaluated using collocated aerosol types obtained from the Aerosol Robotic Network (AERONET) level 1.5 from 23 January 2013 to 28 February 2017. The spatial distribution of VIIRS aerosol types and the aerosol optical depth bias (VIIRS minus AERONET) demonstrate that misidentifying VIIRS aerosol types may lead to VIIRS retrieval being overestimated over the Eastern United States and the developed regions of East Asia, as well as underestimated over Southern Africa, India, and Northeastern China. Approximately 22.33% of VIIRS aerosol types are coincident with that of AERONET. The agreements between VIIRS and AERONET for fine non-absorbing and absorbing aerosol types are approximately 36% and 57%, respectively. However, the agreement between VIIRS and AERONET is extremely low (only 3.51%). The low agreement for coarse absorbing dust may contribute to the poor performance of VIIRS retrieval under the aerosol model (R = 0.61). Results also show that an appropriate aerosol model can improve the retrieval performance of VIIRS over land, particularly for dust type (R increases from 0.61 to 0.72). MDPI 2017-09-05 2017-09 /pmc/articles/PMC5615553/ /pubmed/28872609 http://dx.doi.org/10.3390/ijerph14091016 Text en © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Wang, Wei
Pan, Zengxin
Mao, Feiyue
Gong, Wei
Shen, Longjiao
Evaluation of VIIRS Land Aerosol Model Selection with AERONET Measurements
title Evaluation of VIIRS Land Aerosol Model Selection with AERONET Measurements
title_full Evaluation of VIIRS Land Aerosol Model Selection with AERONET Measurements
title_fullStr Evaluation of VIIRS Land Aerosol Model Selection with AERONET Measurements
title_full_unstemmed Evaluation of VIIRS Land Aerosol Model Selection with AERONET Measurements
title_short Evaluation of VIIRS Land Aerosol Model Selection with AERONET Measurements
title_sort evaluation of viirs land aerosol model selection with aeronet measurements
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5615553/
https://www.ncbi.nlm.nih.gov/pubmed/28872609
http://dx.doi.org/10.3390/ijerph14091016
work_keys_str_mv AT wangwei evaluationofviirslandaerosolmodelselectionwithaeronetmeasurements
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AT gongwei evaluationofviirslandaerosolmodelselectionwithaeronetmeasurements
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