Articles | Volume 18, issue 4
https://doi.org/10.5194/essd-18-2951-2026
https://doi.org/10.5194/essd-18-2951-2026
Data description article
 | 
28 Apr 2026
Data description article |  | 28 Apr 2026

A historical nutrient dataset (1895–2024) for the North Pacific: reconstructed from machine learning and hydrographic observations

Chuanjun Du, Naiwen Zheng, Shuh-Ji Kao, Minhan Dai, Zhimian Cao, Dalin Shi, Qiancheng Li, Hao Wang, Xunlan Luo, and Xiaolin Li

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Short summary
Nutrient levels govern oceanic primary production, but measuring them is labor-intensive and costly. To address this, we used machine learning models to learn the hidden relationships between easy-to-measure ocean properties (like temperature and salinity) and nutrient levels. Applying this model, we created ~ 470 million nutrient data points across the North Pacific from 1895 to 2024. This data will help to understand nutrient dynamics and marine ecosystem variability under climate change.
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