GOBAI: Gridded Ocean Biogeochemistry from Artificial Intelligence

GOBAI-O2

Jonathan D. Sharp, Andrea J. Fassbender, Brendan R. Carter, Gregory C. Johnson, John P. Dunne, and Cristina Schultz

About

GOBAI-O2 is a gridded data product that provides three-dimensional monthly fields of dissolved oxygen in the global ocean from 2004 through 2021. It was constructed by training machine learning algorithms with observations of oxygen concentration ([O2]) from discrete shipboard measurements and autonomous sensors on biogeochemical Argo floats, then applying those machine learning algorithms to three-dimensional monthly gridded fields of temperature and salinity. The algorithms used to produce GOBAI-O2 have been validated using real observations and synthetic data from model output, and the data product itself has been compared against the World Ocean Atlas and selected discrete measurements. Results of these validation and comparison exercises are detailed in Sharp et al. (preprint).

Access

GOBAI-O2 can be accessed from NOAA's National Centers for Environmental Information at https://accession.nodc.noaa.gov/0259304 (doi: 10.25921/z72m-yz67).

Acknowledging use

Please include the data product citation shown below when using GOBAI-O2. In addition, the GOBAI-O2 manuscript may also be cited, which is currently under review for Earth System Science Data.

Data product citation

Sharp, J. D. Fassbender, A. J. Carter, B. R., Johnson, G. C., Schultz, C., Dunne, J. P. (2022). GOBAI-O2: A Global Gridded Monthly Dataset of Ocean Interior Dissolved Oxygen Concentrations Based on Shipboard and Autonomous Observations (NCEI Accession 0259304). v1.0. NOAA National Centers for Environmental Information. Dataset. https://doi.org/10.25921/z72m-yz67.

Manuscript citation

Sharp, J. D. Fassbender, A. J. Carter, B. R., Johnson, G. C., Schultz, C., Dunne, J. P. GOBAI-O2: temporally and spatially resolved fields of ocean interior dissolved oxygen over nearly two decades. In review for Earth System Science Data. https://doi.org/10.5194/essd-2022-308.

Contact: jonathan.sharp@noaa.gov | oar.pmel.gobop@noaa.gov