Articles | Volume 17, issue 6
https://doi.org/10.5194/essd-17-2735-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-17-2735-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
18 Jun 2025
Data description paper |
| 18 Jun 2025
| 18 Jun 2025
A continual-learning-based multilayer perceptron for improved reconstruction of three-dimensional nitrate concentrations
Xiang Yu
Remote Sensing Information and Digital Earth Center, College of Computer Science and Technology, Qingdao University, Qingdao, 266071, China
Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China
Huadong Guo
Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China
Jiahua Zhang
CORRESPONDING AUTHOR
Remote Sensing Information and Digital Earth Center, College of Computer Science and Technology, Qingdao University, Qingdao, 266071, China
Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China
Yi Ma
First Institute of Oceanography Ministry of National Resource, Qingdao, 266061, China
Xiaopeng Wang
Remote Sensing Information and Digital Earth Center, College of Computer Science and Technology, Qingdao University, Qingdao, 266071, China
Guangsheng Liu
Remote Sensing Information and Digital Earth Center, College of Computer Science and Technology, Qingdao University, Qingdao, 266071, China
Mingming Xing
Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China
Department of Biological and Agricultural Engineering, University of California, Davis, CA 95616, USA
Ayalkibet M. Seka
Remote Sensing Information and Digital Earth Center, College of Computer Science and Technology, Qingdao University, Qingdao, 266071, China
Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China
Arba Minch Water Technology Institute, Water Resources Research Center, Arba Minch University, Arba Minch, Ethiopia
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Short summary
Mapping the 3D distribution of oceanic nitrate is challenging. We developed a continual-learning-based multilayer perceptron, integrating prior knowledge from numerical models and BGC-Argo validation to reconstruct a pan-European 3D nitrate field from 2010 to 2023 (0–2000 m depth, monthly, 0.25° horizontal resolution) using sea surface environmental features. This dataset helps bridge observational gaps and enhances understanding of the ocean's interior environment.
Mapping the 3D distribution of oceanic nitrate is challenging. We developed a...
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