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. 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. (2023).
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 published in Earth System Science Data may also be cited.
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). 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. (2023). GOBAI-O2: temporally and spatially resolved fields of ocean interior dissolved oxygen over nearly 2 decades. Earth System Science Data, 15 (10), 4481 - 4518,. https://doi.org/10.5194/essd-15-4481-2023.
Contact: jonathan.sharp@noaa.gov | oar.pmel.gobop@noaa.gov