Cross-scale 3-D thermohaline modeling via dual-residual swin transformer with multisource ocean observations

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Author(s)Wang, An
Author(s)Tang, Zhiwei
Author(s)Huang, Zhanchao
Author(s)Xia, Xiang-Gen
Author(s)Su, Hua
Date Accessioned2026-01-09T22:35:42Z
Date Available2026-01-09T22:35:42Z
Publication Date2025-12-30
Description© 2025 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent. This article was originally published in International Journal of Digital Earth. The version of record is available at: https://doi.org/10.1080/17538947.2025.2607902
AbstractIntegrating multisource Earth observation data and reconstructing subsurface thermohaline structures from remote sensing at global and basin scales will provide a better understanding of oceans. However, previous methods relied on layer-by-layer modeling, which required separate reconstruction of subsurface temperature and salinity fields at different depths, resulting in many models, inefficiency, and weak vertical connections between thermohaline data at different depths. A fast deep neural network-based reconstruction can reduce models and enhance the overall consistency of thermohaline data, which is significant for the reconstruction of ocean environmental variables. This study proposes an improved Swin Transformer approach, i.e. SwinOcean3D, to perform one-shot reconstruction of three-dimensional (3-D) thermohaline structures (upper 1000 m) in different scales of Global (1° × 1°) and Indian Oceans (0.25° × 0.25°) by integrating multisource remote sensing and observation-based ocean products. SwinOcean3D combines the Swin Transformer, U-net, and dual-residual blocks to enhance the representation capability of the global scale, local detailed, and vertical features of ocean thermohaline structures. The significant advantages of SwinOcean3D in the reconstruction of multiscale 3-D thermohaline structures outperform other classical approaches. Furthermore, interpretability experiments suggest that SwinOcean3D can effectively capture the evolution of 3-D thermohaline structures from multisource observations.
SponsorThis study is supported by National Natural Science Foundation of China (42571411), Foreign Cooperation Project of Fujian Province of China (2025I0008), and Public Data Development and Utilisation Technology Innovation and Application Research (CYYJ250202).
CitationAn Wang, Zhiwei Tang , Zhanchao Huang , Xiang-Gen Xia & Hua Su (2026) Cross-scale 3-D thermohaline modeling via dual-residual swin transformer with multisource ocean observations, International Journal of Digital Earth, 19:1, 2607902, DOI: 10.1080/17538947.2025.2607902
ISSN1753-8955
URLhttps://udspace.udel.edu/handle/19716/36829
Languageen_US
PublisherInternational Journal of Digital Earth
dc.rightsAttribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
KeywordsGlobal ocean
Keywords3-D thermohaline structure
Keywordsremote sensing
Keywordsswin transformer
TitleCross-scale 3-D thermohaline modeling via dual-residual swin transformer with multisource ocean observations
TypeArticle
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