PGTransNet: a physics-guided transformer network for 3D ocean temperature and salinity predicting in tropical Pacific
CORRECTION article
PGTransNet: A Physics-guided Transformer Network for 3D Ocean Temperature and Salinity Predicting in Tropical Pacific
Provisionally accepted- 1 College of Computer Science and Technology, National University of Defense Technology, Changsha, China
- 2 College of Meteorology and Oceanography, National University of Defense Technology, Changsha, Anhui Province, China
- 3 School of Computer Science and Engineering, Central South University, Changsha, Hunan Province, China
Text Correction In the published article, there was an error. \textbf{ I found that there is a paragraph and equation repeated in the publication version which need to be deleted. Thus, we need delete the content. Besides, if the equation 5 has been deleted, the remaining equation number (6) (7) (8) in the paper need to be modified into (5) (6) (7). A correction has been made to \textbf{section: Methodology}, \textbf{\textit{subsection: Physics-Guided Information Integrating}}, \textbf{Page 06: Paragraph 4 and 5}. This sentence previously stated:\par \textbf{It's noteworthy that the density of seawater $\rho$ is determined by the reciprocal of the pressure derivative of the Gibbs function~($\textsl{g}$) at constant absolute salinity~(SA) and in situ temperature $T$. Specifically, \begin{equation} \rho = \rho(S_{A},T,P) = (g_{P})^{-1} = (\partial \textsl{g} / \partial P|_{S_{A},T})^{-1} \end{equation} where, $0 \leq S_{A} \leq 120\,g/kg$, $-12\,^\circ\text{C} \leq T \leq 80\,^\circ\text{C}$, $1\,Pa \leq P \leq 100\,MPa$. Compared to the previous standard EOS-80 (Equation of State of Seawater 1980), the TEOS-10 offers broader applicability.}\par The corrected sentence appears below: \textbf{delete}\par
Keywords: Physics-guided machine learning, Spatio-temporal data analysis, Ocean temperature prediction, ocean salinity prediction, Vit
Received: 19 Dec 2024; Accepted: 07 Jan 2025.
Copyright: © 2025 Wu, Bao, Dong, Wang, Zhang, Shao, Zhu and Li. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Senliang Bao, College of Meteorology and Oceanography, National University of Defense Technology, Changsha, Anhui Province, China
Wei Dong, College of Computer Science and Technology, National University of Defense Technology, Changsha, China
Senzhang Wang, School of Computer Science and Engineering, Central South University, Changsha, 130012, Hunan Province, China
Chengcheng Shao, College of Meteorology and Oceanography, National University of Defense Technology, Changsha, Anhui Province, China
Xiaoyong Li, College of Meteorology and Oceanography, National University of Defense Technology, Changsha, Anhui Province, China
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