Antarctic snow melt detection based on the synergy of SSM/I and QuikSCAT

Abstract Microwave radiometer SSM/I (Special Sensor Microwave Imager) data and scatterometer QuikSCAT (Quick Scatterometer) data have been widely used for near-surface snow melt detection based on their sensitivity to liquid water present in snow. The SSM/I data have high reliability and the QuikSCA...

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Published in:Antarctic Science
Main Authors: Li, Xinwu, Wang, Xingdong, Wang, Cheng, Zhang, Lu
Format: Article in Journal/Newspaper
Language:English
Published: Cambridge University Press (CUP) 2017
Subjects:
Online Access:http://dx.doi.org/10.1017/s0954102017000268
https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0954102017000268
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author Li, Xinwu
Wang, Xingdong
Wang, Cheng
Zhang, Lu
author_facet Li, Xinwu
Wang, Xingdong
Wang, Cheng
Zhang, Lu
author_sort Li, Xinwu
collection Cambridge University Press
container_issue 6
container_start_page 561
container_title Antarctic Science
container_volume 29
description Abstract Microwave radiometer SSM/I (Special Sensor Microwave Imager) data and scatterometer QuikSCAT (Quick Scatterometer) data have been widely used for near-surface snow melt detection based on their sensitivity to liquid water present in snow. The SSM/I data have high reliability and the QuikSCAT data have high spatial resolution. In order to improve the accuracy of Antarctic near-surface snow melt detection, we propose a new method based on the synergy of SSM/I and QuikSCAT data, i.e. the snow melt physical model incorporates the complementary advantages of both datasets. Based on comparisons with temperature data from three automatic weather stations, the proposed algorithm improved the accuracy of snow melt detection. The algorithm could also be applied to other regions, which would provide further evidence to support its use and additional data to document changes in the Antarctic due to global climate change.
format Article in Journal/Newspaper
genre Antarc*
Antarctic
Antarctic Science
genre_facet Antarc*
Antarctic
Antarctic Science
geographic Antarctic
The Antarctic
geographic_facet Antarctic
The Antarctic
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op_container_end_page 568
op_doi https://doi.org/10.1017/s0954102017000268
op_rights https://www.cambridge.org/core/terms
op_source Antarctic Science
volume 29, issue 6, page 561-568
ISSN 0954-1020 1365-2079
publishDate 2017
publisher Cambridge University Press (CUP)
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spelling crcambridgeupr:10.1017/s0954102017000268 2025-01-16T19:34:59+00:00 Antarctic snow melt detection based on the synergy of SSM/I and QuikSCAT Li, Xinwu Wang, Xingdong Wang, Cheng Zhang, Lu 2017 http://dx.doi.org/10.1017/s0954102017000268 https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0954102017000268 en eng Cambridge University Press (CUP) https://www.cambridge.org/core/terms Antarctic Science volume 29, issue 6, page 561-568 ISSN 0954-1020 1365-2079 Geology Ecology, Evolution, Behavior and Systematics Oceanography journal-article 2017 crcambridgeupr https://doi.org/10.1017/s0954102017000268 2024-02-08T08:43:48Z Abstract Microwave radiometer SSM/I (Special Sensor Microwave Imager) data and scatterometer QuikSCAT (Quick Scatterometer) data have been widely used for near-surface snow melt detection based on their sensitivity to liquid water present in snow. The SSM/I data have high reliability and the QuikSCAT data have high spatial resolution. In order to improve the accuracy of Antarctic near-surface snow melt detection, we propose a new method based on the synergy of SSM/I and QuikSCAT data, i.e. the snow melt physical model incorporates the complementary advantages of both datasets. Based on comparisons with temperature data from three automatic weather stations, the proposed algorithm improved the accuracy of snow melt detection. The algorithm could also be applied to other regions, which would provide further evidence to support its use and additional data to document changes in the Antarctic due to global climate change. Article in Journal/Newspaper Antarc* Antarctic Antarctic Science Cambridge University Press Antarctic The Antarctic Antarctic Science 29 6 561 568
spellingShingle Geology
Ecology, Evolution, Behavior and Systematics
Oceanography
Li, Xinwu
Wang, Xingdong
Wang, Cheng
Zhang, Lu
Antarctic snow melt detection based on the synergy of SSM/I and QuikSCAT
title Antarctic snow melt detection based on the synergy of SSM/I and QuikSCAT
title_full Antarctic snow melt detection based on the synergy of SSM/I and QuikSCAT
title_fullStr Antarctic snow melt detection based on the synergy of SSM/I and QuikSCAT
title_full_unstemmed Antarctic snow melt detection based on the synergy of SSM/I and QuikSCAT
title_short Antarctic snow melt detection based on the synergy of SSM/I and QuikSCAT
title_sort antarctic snow melt detection based on the synergy of ssm/i and quikscat
topic Geology
Ecology, Evolution, Behavior and Systematics
Oceanography
topic_facet Geology
Ecology, Evolution, Behavior and Systematics
Oceanography
url http://dx.doi.org/10.1017/s0954102017000268
https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0954102017000268