Primary Contact of the Product:
Jonathan D. Sharp
GOBAI-O2
Product Links
GOBAI-O2 : Gridded Ocean Biogeochemistry from Artificial Intelligence - Oxygen.
A gridded data product of ocean oxygen concentrations at monthly resolution on 58 depth levels from 2004 to 2023. GOBAI-O2 is constructed from two types of machine learning algorithms, trained using Argo O2 data and discrete O2 measurements from the GLODAP database, and applied to temperature and salinity grids from Roemmich and Gilson (2009).
| Authors | Affiliation |
|---|---|
| Jonathan D. Sharp | (UW CICOES, NOAA PMEL, USA) |
| Andrea J. Fassbender | (NOAA PMEL, USA) |
| Brendan R. Carter | (UW CICOES, NOAA PMEL, USA) |
| Gregory C. Johnson | (NOAA PMEL, USA) |
| John P. Dunne | (NOAA GFDL, USA) |
| Cristina Schultz | (Northeastern University, USA) |
How to cite BGC-Argo Product
We kindly ask users to cite this product as indicated on the product webpage and DOIs provided in the link below. Proper citation ensures that the use of the dataset is correctly tracked and credited. Please also note that OneArgo data products are freely available without restriction. However, to help us track usage and assess the impact of these products, we request that users include an appropriate acknowledgement in any resulting publications or derived products.In addition to citing the product DOI, please include the following acknowledgement:
"The OneArgo data were collected and made freely available by the International Argo Program and the national programs that contribute to it (https://argo.ucsd.edu, https://www.ocean-ops.org). The OneArgo Program is part of the Global Ocean Observing System."
We greatly appreciate your cooperation in supporting open science and the continued development of these data products.