Articles | Volume 18, issue 7
https://doi.org/10.5194/essd-18-5069-2026
https://doi.org/10.5194/essd-18-5069-2026
Data description article
 | 
20 Jul 2026
Data description article |  | 20 Jul 2026

Jingwei-Nutrients: a global spatiotemporal reconstruction of ocean nutrients (1965–2023) using multi-task deep learning

Zhaokun Wang, Bin Lu, Yi Xin, Takamitsu Ito, Lei Zhou, Lijing Cheng, Yuanlong Li, Xinbing Wang, and Meng Jin

Data sets

Jingwei-Nutrients: A global spatiotemporal reconstruction of ocean nutrients (1965–2023) using multi-task deep learning Zhaokun Wang et al. https://doi.org/10.5281/zenodo.21066027

Argo float data and metadata from Global Data Assembly Centre (Argo GDAC) Argo https://doi.org/10.17882/42182

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Short summary
We present Jingwei-Nutrients, a global monthly data product of ocean nitrate, phosphate, and silicate from 1965 to 2023 down to 2000 meters. Built using a multi-task deep learning framework, it combines sparse historical observations with hydrographic information. This continuous record helps scientists understand marine ecosystems and climate change responses. We also provide the Jingwei web platform (https://jingwei.acemap.info) for dynamic data exploration and visualization without coding.
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