A new retracking algorithm for retrieving sea ice freeboard from Cryosat-2 radar altimeter data during winter-spring transition
A new method called Bézier curve fitting (BCF) for approximating CryoSat-2 (CS-2) SAR-mode waveform is developed to optimize the retrieval of surface elevation of both sea ice and leads for the period of late winter/early spring. We found that the best results are achieved when the retracking points...
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ftawi:oai:epic.awi.de:49654 2024-09-15T18:34:42+00:00 A new retracking algorithm for retrieving sea ice freeboard from Cryosat-2 radar altimeter data during winter-spring transition Shen, Xiaoyi Similä, Markku Dierking, Wolfgang Zhang, Xi Ke, Changqing Liu, Meijie Wang, Manman 2019-05-20 https://epic.awi.de/id/eprint/49654/ https://hdl.handle.net/10013/epic.b1e9e696-70b9-4d6e-94bc-e1c0f6ff76eb unknown MPDI Shen, X. , Similä, M. , Dierking, W. orcid:0000-0002-5031-648X , Zhang, X. , Ke, C. , Liu, M. and Wang, M. (2019) A new retracking algorithm for retrieving sea ice freeboard from Cryosat-2 radar altimeter data during winter-spring transition , Remote Sensing, 11 (10) . doi:10.3390/rs11101194 <https://doi.org/10.3390/rs11101194> , hdl:10013/epic.b1e9e696-70b9-4d6e-94bc-e1c0f6ff76eb EPIC3Remote Sensing, MPDI, 11(10) Article isiRev 2019 ftawi https://doi.org/10.3390/rs11101194 2024-06-24T04:22:11Z A new method called Bézier curve fitting (BCF) for approximating CryoSat-2 (CS-2) SAR-mode waveform is developed to optimize the retrieval of surface elevation of both sea ice and leads for the period of late winter/early spring. We found that the best results are achieved when the retracking points are fixed on positions at which the rise of the fitted Bézier curve reaches 70% of its peak in case of leads, and 50% in case of sea ice. In order to evaluate the proposed retracking algorithm, we compare it to other empirically-based methods currently reported in the literature, namely the threshold first-maximum retracker algorithm (TFMRA) and the European Space Agency (ESA) CS-2 in-depth Level-2 algorithm (L2I). The results of the retracking procedure for the different algorithms are validated using data of the Operation Ice Bridge (OIB) airborne mission. For two OIB campaign periods in March 2015 and April 2016, the mean absolute differences between freeboard values retrieved from CS-2 and OIB data were 9.22 and 7.79 cm when using the BCF method, 10.41 cm and 8.16 cm for TFMRA, and 10.01 cm and 8.42 cm for L2I. This suggests that the sea ice freeboard data can be obtained with a higher accuracy when using the proposed BCF method instead of the TFMRA or the CS-2 L2I algorithm. Article in Journal/Newspaper Sea ice Alfred Wegener Institute for Polar- and Marine Research (AWI): ePIC (electronic Publication Information Center) Remote Sensing 11 10 1194 |
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Open Polar |
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Alfred Wegener Institute for Polar- and Marine Research (AWI): ePIC (electronic Publication Information Center) |
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ftawi |
language |
unknown |
description |
A new method called Bézier curve fitting (BCF) for approximating CryoSat-2 (CS-2) SAR-mode waveform is developed to optimize the retrieval of surface elevation of both sea ice and leads for the period of late winter/early spring. We found that the best results are achieved when the retracking points are fixed on positions at which the rise of the fitted Bézier curve reaches 70% of its peak in case of leads, and 50% in case of sea ice. In order to evaluate the proposed retracking algorithm, we compare it to other empirically-based methods currently reported in the literature, namely the threshold first-maximum retracker algorithm (TFMRA) and the European Space Agency (ESA) CS-2 in-depth Level-2 algorithm (L2I). The results of the retracking procedure for the different algorithms are validated using data of the Operation Ice Bridge (OIB) airborne mission. For two OIB campaign periods in March 2015 and April 2016, the mean absolute differences between freeboard values retrieved from CS-2 and OIB data were 9.22 and 7.79 cm when using the BCF method, 10.41 cm and 8.16 cm for TFMRA, and 10.01 cm and 8.42 cm for L2I. This suggests that the sea ice freeboard data can be obtained with a higher accuracy when using the proposed BCF method instead of the TFMRA or the CS-2 L2I algorithm. |
format |
Article in Journal/Newspaper |
author |
Shen, Xiaoyi Similä, Markku Dierking, Wolfgang Zhang, Xi Ke, Changqing Liu, Meijie Wang, Manman |
spellingShingle |
Shen, Xiaoyi Similä, Markku Dierking, Wolfgang Zhang, Xi Ke, Changqing Liu, Meijie Wang, Manman A new retracking algorithm for retrieving sea ice freeboard from Cryosat-2 radar altimeter data during winter-spring transition |
author_facet |
Shen, Xiaoyi Similä, Markku Dierking, Wolfgang Zhang, Xi Ke, Changqing Liu, Meijie Wang, Manman |
author_sort |
Shen, Xiaoyi |
title |
A new retracking algorithm for retrieving sea ice freeboard from Cryosat-2 radar altimeter data during winter-spring transition |
title_short |
A new retracking algorithm for retrieving sea ice freeboard from Cryosat-2 radar altimeter data during winter-spring transition |
title_full |
A new retracking algorithm for retrieving sea ice freeboard from Cryosat-2 radar altimeter data during winter-spring transition |
title_fullStr |
A new retracking algorithm for retrieving sea ice freeboard from Cryosat-2 radar altimeter data during winter-spring transition |
title_full_unstemmed |
A new retracking algorithm for retrieving sea ice freeboard from Cryosat-2 radar altimeter data during winter-spring transition |
title_sort |
new retracking algorithm for retrieving sea ice freeboard from cryosat-2 radar altimeter data during winter-spring transition |
publisher |
MPDI |
publishDate |
2019 |
url |
https://epic.awi.de/id/eprint/49654/ https://hdl.handle.net/10013/epic.b1e9e696-70b9-4d6e-94bc-e1c0f6ff76eb |
genre |
Sea ice |
genre_facet |
Sea ice |
op_source |
EPIC3Remote Sensing, MPDI, 11(10) |
op_relation |
Shen, X. , Similä, M. , Dierking, W. orcid:0000-0002-5031-648X , Zhang, X. , Ke, C. , Liu, M. and Wang, M. (2019) A new retracking algorithm for retrieving sea ice freeboard from Cryosat-2 radar altimeter data during winter-spring transition , Remote Sensing, 11 (10) . doi:10.3390/rs11101194 <https://doi.org/10.3390/rs11101194> , hdl:10013/epic.b1e9e696-70b9-4d6e-94bc-e1c0f6ff76eb |
op_doi |
https://doi.org/10.3390/rs11101194 |
container_title |
Remote Sensing |
container_volume |
11 |
container_issue |
10 |
container_start_page |
1194 |
_version_ |
1810476649826746368 |