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Collection of dissolved oxygen gridded products obtained from eight machine learning gap-filling algorithms at 1.0° and 0.25° spatial resolution
Citable as data publication
Olivelli, A.; Landschützer, P.; Bushinsky, S.; Flanders Marine Institute; University of Hawai'i at Mānoa; (2026): Collection of dissolved oxygen gridded products obtained from eight machine learning gap-filling algorithms at 1.0° and 0.25° spatial resolution. Marine Data Archive. https://doi.org/10.14284/812
Contact:
Olivelli, Arianna Availability:
 This dataset is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.Description
The files shared in this dataset are associated with the article "Global ocean deoxygenation trends are largely undetectable in machine learning reconstructions due to climate predictor sensitivity" by Olivelli et al., submitted to Machine Learning: Earth. Each file corresponds to one of the eight experiments described in the article and includes dissolved O2 concentrations obtained from a machine learning gap-filling algorithm at monthly resolution between 1993 and 2022 from 0 to 1500 m depth. The spatial resolution is either 1 degree or 0.25 degree, as specified in the file name. Please find more information in the README.rtf file associated with this collection. Scope Themes: Water composition > Dissolved gases Keywords: Biogeochemical cycle · Chemical oceanography · Climate · Dissolved oxygen · World Oceans Geographical coverage World Oceans [Marine Regions] Temporal coverage
1 January 1993 - 31 December 2022 Monthly Parameter
Dissolved oxygen (O2) Methodology
Dissolved oxygen (O2): Machine-learning estimate Contributors
Project
InMOS: Integration of models and observations across scales (InMOS): A novel data synthesis framework for diagnosing the coupled cycles of ocean carbon, oxygen, and heat, more
Funding Foundations, funds and other with scientific goal
Grant agreement ID G-24-66445
Dataset status: Completed
Data type: Data
Data origin: Research: experiment
Metadatarecord created: 2026-08-04
Information last updated: 2026-08-04
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