Complex Principal Component Analysis of Antarctic Ice Sheet Mass Balance

Ice sheet changes of the Antarctic are the result of interactions among the ocean, atmosphere, and ice sheet. Studying the ice sheet mass variations helps us to understand the possible reasons for these changes. We used 164 months of Gravity Recovery and Climate Experiment (GRACE) satellite time-var...

Full description

Bibliographic Details
Published in:Remote Sensing
Main Authors: Jingang Zhan, Hongling Shi, Yong Wang, Yixin Yao
Format: Article in Journal/Newspaper
Language:English
Published: MDPI AG 2021
Subjects:
Q
Online Access:https://doi.org/10.3390/rs13030480
https://doaj.org/article/926d909fadfa40109e7e202454517b6a
id ftdoajarticles:oai:doaj.org/article:926d909fadfa40109e7e202454517b6a
record_format openpolar
spelling ftdoajarticles:oai:doaj.org/article:926d909fadfa40109e7e202454517b6a 2024-01-07T09:40:01+01:00 Complex Principal Component Analysis of Antarctic Ice Sheet Mass Balance Jingang Zhan Hongling Shi Yong Wang Yixin Yao 2021-01-01T00:00:00Z https://doi.org/10.3390/rs13030480 https://doaj.org/article/926d909fadfa40109e7e202454517b6a EN eng MDPI AG https://www.mdpi.com/2072-4292/13/3/480 https://doaj.org/toc/2072-4292 doi:10.3390/rs13030480 2072-4292 https://doaj.org/article/926d909fadfa40109e7e202454517b6a Remote Sensing, Vol 13, Iss 3, p 480 (2021) grace gravity satellite El Niño ice sheet mass balance complex principal component analysis Science Q article 2021 ftdoajarticles https://doi.org/10.3390/rs13030480 2023-12-10T01:42:15Z Ice sheet changes of the Antarctic are the result of interactions among the ocean, atmosphere, and ice sheet. Studying the ice sheet mass variations helps us to understand the possible reasons for these changes. We used 164 months of Gravity Recovery and Climate Experiment (GRACE) satellite time-varying solutions to study the principal components (PCs) of the Antarctic ice sheet mass change and their time-frequency variation. This assessment was based on complex principal component analysis (CPCA) and the wavelet amplitude-period spectrum (WAPS) method to study the PCs and their time-frequency information. The CPCA results revealed the PCs that affect the ice sheet balance, and the wavelet analysis exposed the time-frequency variation of the quasi-periodic signal in each component. The results show that the first PC, which has a linear term and low-frequency signals with periods greater than five years, dominates the variation trend of ice sheet in the Antarctic. The ratio of its variance to the total variance shows that the first PC explains 83.73% of the mass change in the ice sheet. Similar low-frequency signals are also found in the meridional wind at 700 hPa in the South Pacific and the sea surface temperature anomaly (SSTA) in the equatorial Pacific, with the correlation between the low-frequency periodic signal of SSTA in the equatorial Pacific and the first PC of the ice sheet mass change in Antarctica found to be 0.73. The phase signals in the mass change of West Antarctica indicate the upstream propagation of mass loss information over time from the ocean–ice interface to the southward upslope, which mainly reflects ocean-driven factors such as enhanced ice–ocean interaction and the intrusion of warm saline water into the cavities under ice shelves associated with ice sheets which sit on retrograde slopes. Meanwhile, the phase signals in the mass change of East Antarctica indicate the downstream propagation of mass increase information from the South Pole toward Dronning Maud Land, which mainly ... Article in Journal/Newspaper Antarc* Antarctic Antarctica Dronning Maud Land East Antarctica Ice Sheet Ice Shelves South pole South pole West Antarctica Directory of Open Access Journals: DOAJ Articles Antarctic Dronning Maud Land East Antarctica Pacific South Pole The Antarctic West Antarctica Remote Sensing 13 3 480
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic grace gravity satellite
El Niño
ice sheet mass balance
complex principal component analysis
Science
Q
spellingShingle grace gravity satellite
El Niño
ice sheet mass balance
complex principal component analysis
Science
Q
Jingang Zhan
Hongling Shi
Yong Wang
Yixin Yao
Complex Principal Component Analysis of Antarctic Ice Sheet Mass Balance
topic_facet grace gravity satellite
El Niño
ice sheet mass balance
complex principal component analysis
Science
Q
description Ice sheet changes of the Antarctic are the result of interactions among the ocean, atmosphere, and ice sheet. Studying the ice sheet mass variations helps us to understand the possible reasons for these changes. We used 164 months of Gravity Recovery and Climate Experiment (GRACE) satellite time-varying solutions to study the principal components (PCs) of the Antarctic ice sheet mass change and their time-frequency variation. This assessment was based on complex principal component analysis (CPCA) and the wavelet amplitude-period spectrum (WAPS) method to study the PCs and their time-frequency information. The CPCA results revealed the PCs that affect the ice sheet balance, and the wavelet analysis exposed the time-frequency variation of the quasi-periodic signal in each component. The results show that the first PC, which has a linear term and low-frequency signals with periods greater than five years, dominates the variation trend of ice sheet in the Antarctic. The ratio of its variance to the total variance shows that the first PC explains 83.73% of the mass change in the ice sheet. Similar low-frequency signals are also found in the meridional wind at 700 hPa in the South Pacific and the sea surface temperature anomaly (SSTA) in the equatorial Pacific, with the correlation between the low-frequency periodic signal of SSTA in the equatorial Pacific and the first PC of the ice sheet mass change in Antarctica found to be 0.73. The phase signals in the mass change of West Antarctica indicate the upstream propagation of mass loss information over time from the ocean–ice interface to the southward upslope, which mainly reflects ocean-driven factors such as enhanced ice–ocean interaction and the intrusion of warm saline water into the cavities under ice shelves associated with ice sheets which sit on retrograde slopes. Meanwhile, the phase signals in the mass change of East Antarctica indicate the downstream propagation of mass increase information from the South Pole toward Dronning Maud Land, which mainly ...
format Article in Journal/Newspaper
author Jingang Zhan
Hongling Shi
Yong Wang
Yixin Yao
author_facet Jingang Zhan
Hongling Shi
Yong Wang
Yixin Yao
author_sort Jingang Zhan
title Complex Principal Component Analysis of Antarctic Ice Sheet Mass Balance
title_short Complex Principal Component Analysis of Antarctic Ice Sheet Mass Balance
title_full Complex Principal Component Analysis of Antarctic Ice Sheet Mass Balance
title_fullStr Complex Principal Component Analysis of Antarctic Ice Sheet Mass Balance
title_full_unstemmed Complex Principal Component Analysis of Antarctic Ice Sheet Mass Balance
title_sort complex principal component analysis of antarctic ice sheet mass balance
publisher MDPI AG
publishDate 2021
url https://doi.org/10.3390/rs13030480
https://doaj.org/article/926d909fadfa40109e7e202454517b6a
geographic Antarctic
Dronning Maud Land
East Antarctica
Pacific
South Pole
The Antarctic
West Antarctica
geographic_facet Antarctic
Dronning Maud Land
East Antarctica
Pacific
South Pole
The Antarctic
West Antarctica
genre Antarc*
Antarctic
Antarctica
Dronning Maud Land
East Antarctica
Ice Sheet
Ice Shelves
South pole
South pole
West Antarctica
genre_facet Antarc*
Antarctic
Antarctica
Dronning Maud Land
East Antarctica
Ice Sheet
Ice Shelves
South pole
South pole
West Antarctica
op_source Remote Sensing, Vol 13, Iss 3, p 480 (2021)
op_relation https://www.mdpi.com/2072-4292/13/3/480
https://doaj.org/toc/2072-4292
doi:10.3390/rs13030480
2072-4292
https://doaj.org/article/926d909fadfa40109e7e202454517b6a
op_doi https://doi.org/10.3390/rs13030480
container_title Remote Sensing
container_volume 13
container_issue 3
container_start_page 480
_version_ 1787430365859676160