Evaluating Arctic Thin Ice Thickness Retrieved from Latest Version of Multisource Satellite Products

Currently, the performance of sea ice thickness (SIT) data retrieved from multisource satellite products in the Arctic seasonal ice zones remains unclear. This study presented the spatiotemporal intercomparison and evaluation of satellite data, including the latest versions of Soil Moisture and Ocea...

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Main Authors: Huan Li, Jiarui Lian, Yu Zhang, Hailong Guo, Changsheng Chen, Weizeng Shao, Yi Zhou, Deshuai Wang, Song Hu
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Remote Sensing
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Online Access:https://www.mdpi.com/2072-4292/17/10/1680
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author Huan Li
Jiarui Lian
Yu Zhang
Hailong Guo
Changsheng Chen
Weizeng Shao
Yi Zhou
Deshuai Wang
Song Hu
author_facet Huan Li
Jiarui Lian
Yu Zhang
Hailong Guo
Changsheng Chen
Weizeng Shao
Yi Zhou
Deshuai Wang
Song Hu
author_sort Huan Li
collection DOAJ
description Currently, the performance of sea ice thickness (SIT) data retrieved from multisource satellite products in the Arctic seasonal ice zones remains unclear. This study presented the spatiotemporal intercomparison and evaluation of satellite data, including the latest versions of Soil Moisture and Ocean Salinity (SMOS), CryoSat-2, combined CryoSat-2 and SMOS (CS2SMOS), and Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2), specifically focusing on area with mean SIT below 0.5 m. Five evaluation datasets were used. During 2010–2023, SMOS had the smallest mean SIT, with CryoSat-2 showing the largest mean SIT. During 2018–2023, with the inclusion of ICESat-2, SMOS still showed the smallest mean SIT. CryoSat-2 exhibited the largest mean SIT, followed by ICESat-2, CS2SMOS ranked third. Evaluation results indicated that four satellite products generally underestimated SIT. In two periods, SMOS consistently exhibited the weakest performance, which showed a large gap from what was expected in previous studies. In contrast, CS2SMOS demonstrated the highest alignment with five evaluation datasets during 2010–2023, indicating the best overall performance. During 2018–2023, ICESat-2 exhibited the best overall performance with two evaluation datasets. This study refreshes previous knowledge about SMOS in the seasonal ice zones and contributes to further improvements in SIT retrieval.
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spelling doaj-art-a3c57969c98c4cb8941c2da620ca84ca2025-08-20T02:33:55ZengMDPI AGRemote Sensing2072-42922025-05-011710168010.3390/rs17101680Evaluating Arctic Thin Ice Thickness Retrieved from Latest Version of Multisource Satellite ProductsHuan Li0Jiarui Lian1Yu Zhang2Hailong Guo3Changsheng Chen4Weizeng Shao5Yi Zhou6Deshuai Wang7Song Hu8College of Oceanography and Ecological Science, Shanghai Ocean University, Shanghai 201306, ChinaCollege of Meteorology and Oceanography, National University of Defense Technology, Changsha 410073, ChinaCollege of Oceanography and Ecological Science, Shanghai Ocean University, Shanghai 201306, ChinaCollege of Meteorology and Oceanography, National University of Defense Technology, Changsha 410073, ChinaSchool for Marine Science and Technology, University of Massachusetts-Dartmouth, New Bedford, MA 02744, USACollege of Oceanography and Ecological Science, Shanghai Ocean University, Shanghai 201306, ChinaSchool of Oceanography, Shanghai Jiao Tong University, Shanghai 200030, ChinaFirst Institute of Oceanography and Key Laboratory of Marine Science and Numerical Modeling, Ministry of Natural Resources, Qingdao 266061, ChinaCollege of Oceanography and Ecological Science, Shanghai Ocean University, Shanghai 201306, ChinaCurrently, the performance of sea ice thickness (SIT) data retrieved from multisource satellite products in the Arctic seasonal ice zones remains unclear. This study presented the spatiotemporal intercomparison and evaluation of satellite data, including the latest versions of Soil Moisture and Ocean Salinity (SMOS), CryoSat-2, combined CryoSat-2 and SMOS (CS2SMOS), and Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2), specifically focusing on area with mean SIT below 0.5 m. Five evaluation datasets were used. During 2010–2023, SMOS had the smallest mean SIT, with CryoSat-2 showing the largest mean SIT. During 2018–2023, with the inclusion of ICESat-2, SMOS still showed the smallest mean SIT. CryoSat-2 exhibited the largest mean SIT, followed by ICESat-2, CS2SMOS ranked third. Evaluation results indicated that four satellite products generally underestimated SIT. In two periods, SMOS consistently exhibited the weakest performance, which showed a large gap from what was expected in previous studies. In contrast, CS2SMOS demonstrated the highest alignment with five evaluation datasets during 2010–2023, indicating the best overall performance. During 2018–2023, ICESat-2 exhibited the best overall performance with two evaluation datasets. This study refreshes previous knowledge about SMOS in the seasonal ice zones and contributes to further improvements in SIT retrieval.https://www.mdpi.com/2072-4292/17/10/1680sea ice thicknessarcticthin icesatelliteevaluation
spellingShingle Huan Li
Jiarui Lian
Yu Zhang
Hailong Guo
Changsheng Chen
Weizeng Shao
Yi Zhou
Deshuai Wang
Song Hu
Evaluating Arctic Thin Ice Thickness Retrieved from Latest Version of Multisource Satellite Products
Remote Sensing
sea ice thickness
arctic
thin ice
satellite
evaluation
title Evaluating Arctic Thin Ice Thickness Retrieved from Latest Version of Multisource Satellite Products
title_full Evaluating Arctic Thin Ice Thickness Retrieved from Latest Version of Multisource Satellite Products
title_fullStr Evaluating Arctic Thin Ice Thickness Retrieved from Latest Version of Multisource Satellite Products
title_full_unstemmed Evaluating Arctic Thin Ice Thickness Retrieved from Latest Version of Multisource Satellite Products
title_short Evaluating Arctic Thin Ice Thickness Retrieved from Latest Version of Multisource Satellite Products
title_sort evaluating arctic thin ice thickness retrieved from latest version of multisource satellite products
topic sea ice thickness
arctic
thin ice
satellite
evaluation
url https://www.mdpi.com/2072-4292/17/10/1680
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