Elevation Change Derived from SARAL/ALtiKa Altimetric Mission: Quality Assessment and Performance of the Ka-Band
The waveform retracking algorithm is a key factor that affects the accuracy of elevation change from satellite altimetry over an ice sheet. The elevation change results from four waveform retracker algorithms (ICE1/ICE2/Sea Ice/OCEAN) provided by the Satellite with ARgos and ALtiKa (SARAL/ALtiKa) da...
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ftdoajarticles:oai:doaj.org/article:07d7561721b74ecaa37e9e9a6b2fc693 2023-05-15T16:27:10+02:00 Elevation Change Derived from SARAL/ALtiKa Altimetric Mission: Quality Assessment and Performance of the Ka-Band Quanming Yang Yuande Yang Zemin Wang Baojun Zhang Hu Jiang 2018-04-01T00:00:00Z https://doi.org/10.3390/rs10040539 https://doaj.org/article/07d7561721b74ecaa37e9e9a6b2fc693 EN eng MDPI AG http://www.mdpi.com/2072-4292/10/4/539 https://doaj.org/toc/2072-4292 2072-4292 doi:10.3390/rs10040539 https://doaj.org/article/07d7561721b74ecaa37e9e9a6b2fc693 Remote Sensing, Vol 10, Iss 4, p 539 (2018) waveform retracking ICEBridge SARAL elevation change Greenland slope Science Q article 2018 ftdoajarticles https://doi.org/10.3390/rs10040539 2022-12-31T12:47:42Z The waveform retracking algorithm is a key factor that affects the accuracy of elevation change from satellite altimetry over an ice sheet. The elevation change results from four waveform retracker algorithms (ICE1/ICE2/Sea Ice/OCEAN) provided by the Satellite with ARgos and ALtiKa (SARAL/ALtiKa) data were compared using repeated SARAL data between March 2013 and April 2016 to determine the optimal retracker in the crossovers of descending and ascending orbits over a Greenland ice sheet (GrIS). The ICE1 provided slightly better results than the three other algorithms with the lowest standard deviation (SD) of 0.30 m year−1. Further comparison was also conducted between the Satellite with ARgos and ALtiKa (SARAL) and Operation ICEBridge laser data, thereby indicating that ICE1 was the best retracker with an Root Mean Square Error (RMSE) of 0.43 m year−1. The distribution of elevation change rate and uncertainties over Greenland from SARAL were presented using the selected ICE1 retracker with a volume loss of 40 ± 12 km3 year−1. This volume loss did not include the fast-changing coastal areas of the GrIS. A large thinning was observed in Jakobshavn Isbræ, and a trend that extended far inland was also found from 2013–2016. Furthermore, a melting ice sheet was observed in the large areas northwest over the GrIS. Article in Journal/Newspaper Greenland Ice Sheet Jakobshavn Jakobshavn isbræ Sea ice Directory of Open Access Journals: DOAJ Articles Greenland Jakobshavn Isbræ ENVELOPE(-49.917,-49.917,69.167,69.167) Remote Sensing 10 4 539 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
waveform retracking ICEBridge SARAL elevation change Greenland slope Science Q |
spellingShingle |
waveform retracking ICEBridge SARAL elevation change Greenland slope Science Q Quanming Yang Yuande Yang Zemin Wang Baojun Zhang Hu Jiang Elevation Change Derived from SARAL/ALtiKa Altimetric Mission: Quality Assessment and Performance of the Ka-Band |
topic_facet |
waveform retracking ICEBridge SARAL elevation change Greenland slope Science Q |
description |
The waveform retracking algorithm is a key factor that affects the accuracy of elevation change from satellite altimetry over an ice sheet. The elevation change results from four waveform retracker algorithms (ICE1/ICE2/Sea Ice/OCEAN) provided by the Satellite with ARgos and ALtiKa (SARAL/ALtiKa) data were compared using repeated SARAL data between March 2013 and April 2016 to determine the optimal retracker in the crossovers of descending and ascending orbits over a Greenland ice sheet (GrIS). The ICE1 provided slightly better results than the three other algorithms with the lowest standard deviation (SD) of 0.30 m year−1. Further comparison was also conducted between the Satellite with ARgos and ALtiKa (SARAL) and Operation ICEBridge laser data, thereby indicating that ICE1 was the best retracker with an Root Mean Square Error (RMSE) of 0.43 m year−1. The distribution of elevation change rate and uncertainties over Greenland from SARAL were presented using the selected ICE1 retracker with a volume loss of 40 ± 12 km3 year−1. This volume loss did not include the fast-changing coastal areas of the GrIS. A large thinning was observed in Jakobshavn Isbræ, and a trend that extended far inland was also found from 2013–2016. Furthermore, a melting ice sheet was observed in the large areas northwest over the GrIS. |
format |
Article in Journal/Newspaper |
author |
Quanming Yang Yuande Yang Zemin Wang Baojun Zhang Hu Jiang |
author_facet |
Quanming Yang Yuande Yang Zemin Wang Baojun Zhang Hu Jiang |
author_sort |
Quanming Yang |
title |
Elevation Change Derived from SARAL/ALtiKa Altimetric Mission: Quality Assessment and Performance of the Ka-Band |
title_short |
Elevation Change Derived from SARAL/ALtiKa Altimetric Mission: Quality Assessment and Performance of the Ka-Band |
title_full |
Elevation Change Derived from SARAL/ALtiKa Altimetric Mission: Quality Assessment and Performance of the Ka-Band |
title_fullStr |
Elevation Change Derived from SARAL/ALtiKa Altimetric Mission: Quality Assessment and Performance of the Ka-Band |
title_full_unstemmed |
Elevation Change Derived from SARAL/ALtiKa Altimetric Mission: Quality Assessment and Performance of the Ka-Band |
title_sort |
elevation change derived from saral/altika altimetric mission: quality assessment and performance of the ka-band |
publisher |
MDPI AG |
publishDate |
2018 |
url |
https://doi.org/10.3390/rs10040539 https://doaj.org/article/07d7561721b74ecaa37e9e9a6b2fc693 |
long_lat |
ENVELOPE(-49.917,-49.917,69.167,69.167) |
geographic |
Greenland Jakobshavn Isbræ |
geographic_facet |
Greenland Jakobshavn Isbræ |
genre |
Greenland Ice Sheet Jakobshavn Jakobshavn isbræ Sea ice |
genre_facet |
Greenland Ice Sheet Jakobshavn Jakobshavn isbræ Sea ice |
op_source |
Remote Sensing, Vol 10, Iss 4, p 539 (2018) |
op_relation |
http://www.mdpi.com/2072-4292/10/4/539 https://doaj.org/toc/2072-4292 2072-4292 doi:10.3390/rs10040539 https://doaj.org/article/07d7561721b74ecaa37e9e9a6b2fc693 |
op_doi |
https://doi.org/10.3390/rs10040539 |
container_title |
Remote Sensing |
container_volume |
10 |
container_issue |
4 |
container_start_page |
539 |
_version_ |
1766016259359506432 |