Aerosol Optical Depth over the Arctic Snow-Covered Regions Derived from Dual-Viewing Satellite Observations

Aerosol properties over the Arctic snow-covered regions are sparsely provided by temporal and spatially limited in situ measurements or active Lidar observations. This introduces large uncertainties for the understanding of aerosol effects on Arctic climate change. In this paper, aerosol optical dep...

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Published in:Remote Sensing
Main Authors: Zheng Shi, Tingyan Xing, Jie Guang, Yong Xue, Yahui Che
Format: Text
Language:English
Published: Multidisciplinary Digital Publishing Institute 2019
Subjects:
AOD
Online Access:https://doi.org/10.3390/rs11080891
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spelling ftmdpi:oai:mdpi.com:/2072-4292/11/8/891/ 2023-08-20T04:03:27+02:00 Aerosol Optical Depth over the Arctic Snow-Covered Regions Derived from Dual-Viewing Satellite Observations Zheng Shi Tingyan Xing Jie Guang Yong Xue Yahui Che agris 2019-04-12 application/pdf https://doi.org/10.3390/rs11080891 EN eng Multidisciplinary Digital Publishing Institute Atmospheric Remote Sensing https://dx.doi.org/10.3390/rs11080891 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 11; Issue 8; Pages: 891 Arctic AATSR AOD snow Text 2019 ftmdpi https://doi.org/10.3390/rs11080891 2023-07-31T22:11:24Z Aerosol properties over the Arctic snow-covered regions are sparsely provided by temporal and spatially limited in situ measurements or active Lidar observations. This introduces large uncertainties for the understanding of aerosol effects on Arctic climate change. In this paper, aerosol optical depth (AOD) is derived using the advanced along-track scanning radiometer (AATSR) instrument. The basic idea is to utilize the dual-viewing observation capability of AATSR to reduce the impacts of AOD uncertainties introduced by the absolute wavelength-dependent error on surface reflectance estimation. AOD is derived assuming that the satellite observed surface reflectance ratio can be well characterized by a snow bidirectional reflectance distribution function (BRDF) model with a certain correction direct from satellite top of the atmosphere (TOA) observation. The aerosol types include an Arctic haze aerosol obtained from campaign measurement and Arctic background aerosol (maritime aerosol) types. The proper aerosol type is selected during the iteration step based on the minimization residual. The algorithm has been used over Spitsbergen for the spring period (April–May) and the AOD spatial distribution indicates that the retrieval AOD can capture the Arctic haze event. The comparison with AERONET observations shows promising results, with a correlation coefficient R = 0.70. The time series analysis shows no systematical biases between AATSR retrieved AOD and AERONET observed ones. Text Arctic Climate change Spitsbergen MDPI Open Access Publishing Arctic Remote Sensing 11 8 891
institution Open Polar
collection MDPI Open Access Publishing
op_collection_id ftmdpi
language English
topic Arctic
AATSR
AOD
snow
spellingShingle Arctic
AATSR
AOD
snow
Zheng Shi
Tingyan Xing
Jie Guang
Yong Xue
Yahui Che
Aerosol Optical Depth over the Arctic Snow-Covered Regions Derived from Dual-Viewing Satellite Observations
topic_facet Arctic
AATSR
AOD
snow
description Aerosol properties over the Arctic snow-covered regions are sparsely provided by temporal and spatially limited in situ measurements or active Lidar observations. This introduces large uncertainties for the understanding of aerosol effects on Arctic climate change. In this paper, aerosol optical depth (AOD) is derived using the advanced along-track scanning radiometer (AATSR) instrument. The basic idea is to utilize the dual-viewing observation capability of AATSR to reduce the impacts of AOD uncertainties introduced by the absolute wavelength-dependent error on surface reflectance estimation. AOD is derived assuming that the satellite observed surface reflectance ratio can be well characterized by a snow bidirectional reflectance distribution function (BRDF) model with a certain correction direct from satellite top of the atmosphere (TOA) observation. The aerosol types include an Arctic haze aerosol obtained from campaign measurement and Arctic background aerosol (maritime aerosol) types. The proper aerosol type is selected during the iteration step based on the minimization residual. The algorithm has been used over Spitsbergen for the spring period (April–May) and the AOD spatial distribution indicates that the retrieval AOD can capture the Arctic haze event. The comparison with AERONET observations shows promising results, with a correlation coefficient R = 0.70. The time series analysis shows no systematical biases between AATSR retrieved AOD and AERONET observed ones.
format Text
author Zheng Shi
Tingyan Xing
Jie Guang
Yong Xue
Yahui Che
author_facet Zheng Shi
Tingyan Xing
Jie Guang
Yong Xue
Yahui Che
author_sort Zheng Shi
title Aerosol Optical Depth over the Arctic Snow-Covered Regions Derived from Dual-Viewing Satellite Observations
title_short Aerosol Optical Depth over the Arctic Snow-Covered Regions Derived from Dual-Viewing Satellite Observations
title_full Aerosol Optical Depth over the Arctic Snow-Covered Regions Derived from Dual-Viewing Satellite Observations
title_fullStr Aerosol Optical Depth over the Arctic Snow-Covered Regions Derived from Dual-Viewing Satellite Observations
title_full_unstemmed Aerosol Optical Depth over the Arctic Snow-Covered Regions Derived from Dual-Viewing Satellite Observations
title_sort aerosol optical depth over the arctic snow-covered regions derived from dual-viewing satellite observations
publisher Multidisciplinary Digital Publishing Institute
publishDate 2019
url https://doi.org/10.3390/rs11080891
op_coverage agris
geographic Arctic
geographic_facet Arctic
genre Arctic
Climate change
Spitsbergen
genre_facet Arctic
Climate change
Spitsbergen
op_source Remote Sensing; Volume 11; Issue 8; Pages: 891
op_relation Atmospheric Remote Sensing
https://dx.doi.org/10.3390/rs11080891
op_rights https://creativecommons.org/licenses/by/4.0/
op_doi https://doi.org/10.3390/rs11080891
container_title Remote Sensing
container_volume 11
container_issue 8
container_start_page 891
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