Articles | Volume 17, issue 6
https://doi.org/10.5194/essd-17-2735-2025
https://doi.org/10.5194/essd-17-2735-2025
Data description paper
 | 
18 Jun 2025
Data description paper |  | 18 Jun 2025

A continual-learning-based multilayer perceptron for improved reconstruction of three-dimensional nitrate concentrations

Xiang Yu, Huadong Guo, Jiahua Zhang, Yi Ma, Xiaopeng Wang, Guangsheng Liu, Mingming Xing, Nuo Xu, and Ayalkibet M. Seka

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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.
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