Characteristics of the Greenland Ice Sheet Mass Variations Revealed by GRACE/GRACE Follow-On Gravimetry

As a major contributor to global mean sea-level rise, the Greenland ice sheet (GrIS) and the patterns of its mass change have attracted wide attention. Based on Gravity Recovery and Climate Experiment (GRACE)/GRACE Follow-On (GRACE-FO) gravimetry data, we computed monthly non-cumulative mass change...

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Published in:Remote Sensing
Main Authors: Peisi Shang, Xiaoli Su, Zhicai Luo
Format: Article in Journal/Newspaper
Language:English
Published: MDPI AG 2022
Subjects:
Q
Online Access:https://doi.org/10.3390/rs14184442
https://doaj.org/article/ca6595043364456dbb361410612c8a69
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spelling ftdoajarticles:oai:doaj.org/article:ca6595043364456dbb361410612c8a69 2023-05-15T15:08:09+02:00 Characteristics of the Greenland Ice Sheet Mass Variations Revealed by GRACE/GRACE Follow-On Gravimetry Peisi Shang Xiaoli Su Zhicai Luo 2022-09-01T00:00:00Z https://doi.org/10.3390/rs14184442 https://doaj.org/article/ca6595043364456dbb361410612c8a69 EN eng MDPI AG https://www.mdpi.com/2072-4292/14/18/4442 https://doaj.org/toc/2072-4292 doi:10.3390/rs14184442 2072-4292 https://doaj.org/article/ca6595043364456dbb361410612c8a69 Remote Sensing, Vol 14, Iss 4442, p 4442 (2022) Greenland ice sheet GRACE/GRACE-FO gravimetry mass variations Science Q article 2022 ftdoajarticles https://doi.org/10.3390/rs14184442 2022-12-30T19:57:44Z As a major contributor to global mean sea-level rise, the Greenland ice sheet (GrIS) and the patterns of its mass change have attracted wide attention. Based on Gravity Recovery and Climate Experiment (GRACE)/GRACE Follow-On (GRACE-FO) gravimetry data, we computed monthly non-cumulative mass change time series of the GrIS, which agree with those from the mass budget method confirming the reliability of GRACE-FO-derived mass change. Over the GrIS, mass was mainly gained in winter, followed by spring. It primarily lost mass in summer, with the percentage of summer mass loss versus the corresponding annual mass loss ranging from 61% to 96%. We report that spring mass loss has become more frequent since 2015, and autumn mass gain occurred more frequently after 2014. By separating mass gain from mass loss at the annual timescale, we find that both the mass gain and mass loss showed a slightly increasing trend during 2003–2020, which might be a response to the ongoing Arctic warming. Summer mass variations highly correlated with the summer North Atlantic Oscillation index are dominated by temperature-associated precipitation and meltwater runoff. This study suggests that long-term observations would be necessary to better understand patterns of the GrIS mass variations in future. Article in Journal/Newspaper Arctic Greenland Ice Sheet North Atlantic North Atlantic oscillation Directory of Open Access Journals: DOAJ Articles Arctic Greenland Remote Sensing 14 18 4442
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic Greenland ice sheet
GRACE/GRACE-FO gravimetry
mass variations
Science
Q
spellingShingle Greenland ice sheet
GRACE/GRACE-FO gravimetry
mass variations
Science
Q
Peisi Shang
Xiaoli Su
Zhicai Luo
Characteristics of the Greenland Ice Sheet Mass Variations Revealed by GRACE/GRACE Follow-On Gravimetry
topic_facet Greenland ice sheet
GRACE/GRACE-FO gravimetry
mass variations
Science
Q
description As a major contributor to global mean sea-level rise, the Greenland ice sheet (GrIS) and the patterns of its mass change have attracted wide attention. Based on Gravity Recovery and Climate Experiment (GRACE)/GRACE Follow-On (GRACE-FO) gravimetry data, we computed monthly non-cumulative mass change time series of the GrIS, which agree with those from the mass budget method confirming the reliability of GRACE-FO-derived mass change. Over the GrIS, mass was mainly gained in winter, followed by spring. It primarily lost mass in summer, with the percentage of summer mass loss versus the corresponding annual mass loss ranging from 61% to 96%. We report that spring mass loss has become more frequent since 2015, and autumn mass gain occurred more frequently after 2014. By separating mass gain from mass loss at the annual timescale, we find that both the mass gain and mass loss showed a slightly increasing trend during 2003–2020, which might be a response to the ongoing Arctic warming. Summer mass variations highly correlated with the summer North Atlantic Oscillation index are dominated by temperature-associated precipitation and meltwater runoff. This study suggests that long-term observations would be necessary to better understand patterns of the GrIS mass variations in future.
format Article in Journal/Newspaper
author Peisi Shang
Xiaoli Su
Zhicai Luo
author_facet Peisi Shang
Xiaoli Su
Zhicai Luo
author_sort Peisi Shang
title Characteristics of the Greenland Ice Sheet Mass Variations Revealed by GRACE/GRACE Follow-On Gravimetry
title_short Characteristics of the Greenland Ice Sheet Mass Variations Revealed by GRACE/GRACE Follow-On Gravimetry
title_full Characteristics of the Greenland Ice Sheet Mass Variations Revealed by GRACE/GRACE Follow-On Gravimetry
title_fullStr Characteristics of the Greenland Ice Sheet Mass Variations Revealed by GRACE/GRACE Follow-On Gravimetry
title_full_unstemmed Characteristics of the Greenland Ice Sheet Mass Variations Revealed by GRACE/GRACE Follow-On Gravimetry
title_sort characteristics of the greenland ice sheet mass variations revealed by grace/grace follow-on gravimetry
publisher MDPI AG
publishDate 2022
url https://doi.org/10.3390/rs14184442
https://doaj.org/article/ca6595043364456dbb361410612c8a69
geographic Arctic
Greenland
geographic_facet Arctic
Greenland
genre Arctic
Greenland
Ice Sheet
North Atlantic
North Atlantic oscillation
genre_facet Arctic
Greenland
Ice Sheet
North Atlantic
North Atlantic oscillation
op_source Remote Sensing, Vol 14, Iss 4442, p 4442 (2022)
op_relation https://www.mdpi.com/2072-4292/14/18/4442
https://doaj.org/toc/2072-4292
doi:10.3390/rs14184442
2072-4292
https://doaj.org/article/ca6595043364456dbb361410612c8a69
op_doi https://doi.org/10.3390/rs14184442
container_title Remote Sensing
container_volume 14
container_issue 18
container_start_page 4442
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