Decadal Changes in Greenland Ice Sheet Firn Aquifers from Radar Scatterometer
Surface meltwater runoff is believed to be the main cause of the alarming mass loss in the Greenland Ice Sheet (GrIS); however, recent research has shown that a large amount of meltwater is not directly drained or refrozen but stored in the form of firn aquifers (FAs) in the interior of the GrIS. Mo...
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ftmdpi:oai:mdpi.com:/2072-4292/14/9/2134/ 2023-08-20T04:06:52+02:00 Decadal Changes in Greenland Ice Sheet Firn Aquifers from Radar Scatterometer Xinyi Shang Xiao Cheng Lei Zheng Qi Liang Zhaohui Chi 2022-04-29 application/pdf https://doi.org/10.3390/rs14092134 EN eng Multidisciplinary Digital Publishing Institute Remote Sensing in Geology, Geomorphology and Hydrology https://dx.doi.org/10.3390/rs14092134 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 14; Issue 9; Pages: 2134 Greenland firn aquifers random forests radar scatterometer surface snowmelt Text 2022 ftmdpi https://doi.org/10.3390/rs14092134 2023-08-01T04:54:46Z Surface meltwater runoff is believed to be the main cause of the alarming mass loss in the Greenland Ice Sheet (GrIS); however, recent research has shown that a large amount of meltwater is not directly drained or refrozen but stored in the form of firn aquifers (FAs) in the interior of the GrIS. Monitoring the changes in FAs over the GrIS is of great importance to evaluate the stability and mass balance of the ice sheet. This is challenging because FAs are not visible on the surface and the direct measurements are lacking. A new method is proposed to map FAs during the 2010–2020 period by using the C-band Advanced Scatterometer (ASCAT) data based on the Random Forests classification algorithm with the aid of measurements from the NASA Operation IceBridge (OIB) program. Melt days (MD), melt intensity (MI), and winter mean backscatter (WM) parameters derived from the ASCAT data are used as the input vectors for the Random Forests classification algorithm. The accuracy of the classification model is assessed by ten-fold cross-validation, and the overall accuracy and Kappa coefficient are 97.49% and 0.72 respectively. The results show that FAs reached the maximum in 2015, and the accumulative area of FAs from 2010 to 2020 is 56,477 km2, which is 3.3% of the GrIS area. This study provides a way to investigate the long-term dynamics in FAs which have great significance for understanding the state of subsurface firn and subglacial hydrological systems. Text Greenland Ice Sheet NASA Operation IceBridge (OIB) MDPI Open Access Publishing Greenland Remote Sensing 14 9 2134 |
institution |
Open Polar |
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MDPI Open Access Publishing |
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ftmdpi |
language |
English |
topic |
Greenland firn aquifers random forests radar scatterometer surface snowmelt |
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Greenland firn aquifers random forests radar scatterometer surface snowmelt Xinyi Shang Xiao Cheng Lei Zheng Qi Liang Zhaohui Chi Decadal Changes in Greenland Ice Sheet Firn Aquifers from Radar Scatterometer |
topic_facet |
Greenland firn aquifers random forests radar scatterometer surface snowmelt |
description |
Surface meltwater runoff is believed to be the main cause of the alarming mass loss in the Greenland Ice Sheet (GrIS); however, recent research has shown that a large amount of meltwater is not directly drained or refrozen but stored in the form of firn aquifers (FAs) in the interior of the GrIS. Monitoring the changes in FAs over the GrIS is of great importance to evaluate the stability and mass balance of the ice sheet. This is challenging because FAs are not visible on the surface and the direct measurements are lacking. A new method is proposed to map FAs during the 2010–2020 period by using the C-band Advanced Scatterometer (ASCAT) data based on the Random Forests classification algorithm with the aid of measurements from the NASA Operation IceBridge (OIB) program. Melt days (MD), melt intensity (MI), and winter mean backscatter (WM) parameters derived from the ASCAT data are used as the input vectors for the Random Forests classification algorithm. The accuracy of the classification model is assessed by ten-fold cross-validation, and the overall accuracy and Kappa coefficient are 97.49% and 0.72 respectively. The results show that FAs reached the maximum in 2015, and the accumulative area of FAs from 2010 to 2020 is 56,477 km2, which is 3.3% of the GrIS area. This study provides a way to investigate the long-term dynamics in FAs which have great significance for understanding the state of subsurface firn and subglacial hydrological systems. |
format |
Text |
author |
Xinyi Shang Xiao Cheng Lei Zheng Qi Liang Zhaohui Chi |
author_facet |
Xinyi Shang Xiao Cheng Lei Zheng Qi Liang Zhaohui Chi |
author_sort |
Xinyi Shang |
title |
Decadal Changes in Greenland Ice Sheet Firn Aquifers from Radar Scatterometer |
title_short |
Decadal Changes in Greenland Ice Sheet Firn Aquifers from Radar Scatterometer |
title_full |
Decadal Changes in Greenland Ice Sheet Firn Aquifers from Radar Scatterometer |
title_fullStr |
Decadal Changes in Greenland Ice Sheet Firn Aquifers from Radar Scatterometer |
title_full_unstemmed |
Decadal Changes in Greenland Ice Sheet Firn Aquifers from Radar Scatterometer |
title_sort |
decadal changes in greenland ice sheet firn aquifers from radar scatterometer |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2022 |
url |
https://doi.org/10.3390/rs14092134 |
geographic |
Greenland |
geographic_facet |
Greenland |
genre |
Greenland Ice Sheet NASA Operation IceBridge (OIB) |
genre_facet |
Greenland Ice Sheet NASA Operation IceBridge (OIB) |
op_source |
Remote Sensing; Volume 14; Issue 9; Pages: 2134 |
op_relation |
Remote Sensing in Geology, Geomorphology and Hydrology https://dx.doi.org/10.3390/rs14092134 |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.3390/rs14092134 |
container_title |
Remote Sensing |
container_volume |
14 |
container_issue |
9 |
container_start_page |
2134 |
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1774718209624113152 |